Overview

Brought to you by YData

Dataset statistics

Number of variables	55
Number of observations	999
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	4.4 MiB
Average record size in memory	4.5 KiB

Variable types

Text	23
Numeric	2
Categorical	8
Boolean	22

Alerts

`Authority_Present` is highly overall correlated with `Visibility`	High correlation
`Clarity_and_Conciseness_Value` is highly overall correlated with `Length_General_Assessment` and 2 other fields	High correlation
`Contains_Colon` is highly overall correlated with `Visibility`	High correlation
`Contains_Exclamation_Mark` is highly overall correlated with `Visibility`	High correlation
`Contains_Hyphen` is highly overall correlated with `Visibility`	High correlation
`Contains_Numbers` is highly overall correlated with `Visibility`	High correlation
`Contains_Question_Mark` is highly overall correlated with `Ends_With_Question_Mark` and 2 other fields	High correlation
`Contains_Quotes` is highly overall correlated with `Main_Classification` and 1 other fields	High correlation
`Curiosity_Present` is highly overall correlated with `Visibility`	High correlation
`Economic_Benefit_Present` is highly overall correlated with `Visibility`	High correlation
`Ends_With_Question_Mark` is highly overall correlated with `Contains_Question_Mark` and 2 other fields	High correlation
`Exclusivity_Present` is highly overall correlated with `Exclusivity_Words` and 1 other fields	High correlation
`Exclusivity_Words` is highly overall correlated with `Exclusivity_Present` and 1 other fields	High correlation
`Fear_Concern_Present` is highly overall correlated with `Main_Category` and 1 other fields	High correlation
`Hope_Optimism_Present` is highly overall correlated with `Solution_Present` and 1 other fields	High correlation
`Indignation_Controversy_Present` is highly overall correlated with `Visibility`	High correlation
`Length_General_Assessment` is highly overall correlated with `Clarity_and_Conciseness_Value` and 2 other fields	High correlation
`Length_Number_of_Characters` is highly overall correlated with `Clarity_and_Conciseness_Value` and 2 other fields	High correlation
`Main_Category` is highly overall correlated with `Fear_Concern_Present` and 2 other fields	High correlation
`Main_Classification` is highly overall correlated with `Contains_Question_Mark` and 4 other fields	High correlation
`National_Relevance_Present` is highly overall correlated with `Main_Category` and 1 other fields	High correlation
`Originality_and_Differentiation_Value` is highly overall correlated with `Surprise_Awe_Present` and 1 other fields	High correlation
`Personal_Identification_Present` is highly overall correlated with `Visibility`	High correlation
`Prohibition_Restriction_Present` is highly overall correlated with `Visibility`	High correlation
`Recognized_Brand_Present` is highly overall correlated with `Visibility`	High correlation
`Relevance_and_Timeliness_Value` is highly overall correlated with `Visibility`	High correlation
`Solution_Present` is highly overall correlated with `Hope_Optimism_Present` and 1 other fields	High correlation
`Starts_With_Number` is highly overall correlated with `Main_Classification` and 1 other fields	High correlation
`Strategic_Keyword_Usage_Value` is highly overall correlated with `Length_Number_of_Characters` and 1 other fields	High correlation
`Surprise_Awe_Present` is highly overall correlated with `Originality_and_Differentiation_Value` and 1 other fields	High correlation
`Temporal_Urgency_Present` is highly overall correlated with `Visibility`	High correlation
`Visibility` is highly overall correlated with `Authority_Present` and 29 other fields	High correlation
`Clarity_and_Conciseness_Value` is highly imbalanced (87.0%)	Imbalance
`Relevance_and_Timeliness_Value` is highly imbalanced (72.6%)	Imbalance
`Strategic_Keyword_Usage_Value` is highly imbalanced (86.4%)	Imbalance
`Contains_Question_Mark` is highly imbalanced (75.8%)	Imbalance
`Contains_Exclamation_Mark` is highly imbalanced (97.1%)	Imbalance
`Starts_With_Number` is highly imbalanced (57.3%)	Imbalance
`Ends_With_Question_Mark` is highly imbalanced (82.1%)	Imbalance
`Length_General_Assessment` is highly imbalanced (63.4%)	Imbalance
`Exclusivity_Present` is highly imbalanced (77.1%)	Imbalance
`Exclusivity_Words` is highly imbalanced (91.8%)	Imbalance
`Prohibition_Restriction_Present` is highly imbalanced (62.3%)	Imbalance
`Title` has unique values	Unique
`Visibility` has unique values	Unique
`Cleaned_Headline` has unique values	Unique
`Relevance_and_Timeliness_Comment` has unique values	Unique
`Strategic_Keyword_Usage_Comment` has unique values	Unique
`Originality_and_Differentiation_Comment` has unique values	Unique

Reproduction

Analysis started	2025-07-03 07:06:56.407786
Analysis finished	2025-07-03 07:07:19.551717
Duration	23.14 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

Title
Text

Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	180.1 KiB

Length

Max length	263
Median length	145
Mean length	83.154154
Min length	20

Characters and Unicode

Total characters	83071
Distinct characters	92
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	999 ?
Unique (%)	100.0%

Sample

1st row	Ford is forced to immediately shut down factories and halt car production as CEO admits 'day to day' struggle for brand
2nd row	New U.S. Driving License Rule for Seniors Begins July 2025 - Essential Changes for Drivers Aged 70 and Above
3rd row	Cadets who met all Air Force Academy graduation standards denied commissions because they’re transgender
4th row	The DMV confirms it - The United States is ending the benefit that allowed drivers to drive with an expired license without immediate renewal - millions of drivers will have to renew urgently
5th row	McDonald's Removing 1 Breakfast Menu Item for Good on July 2

Value	Count	Frequency (%)
to	418	3.0%
the	372	2.7%
in	274	2.0%
of	210	1.5%
a	197	1.4%
and	195	1.4%
for	194	1.4%
new	143	1.0%
with	104	0.8%
is	98	0.7%
Other values (4244)	11532	83.9%

Most occurring characters

Value	Count	Frequency (%)
	12738	15.3%
e	7675	9.2%
a	4983	6.0%
o	4803	5.8%
t	4685	5.6%
r	4540	5.5%
n	4437	5.3%
i	4398	5.3%
s	4306	5.2%
l	2860	3.4%
Other values (82)	27646	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	83071	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	12738	15.3%
e	7675	9.2%
a	4983	6.0%
o	4803	5.8%
t	4685	5.6%
r	4540	5.5%
n	4437	5.3%
i	4398	5.3%
s	4306	5.2%
l	2860	3.4%
Other values (82)	27646	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	83071	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	12738	15.3%
e	7675	9.2%
a	4983	6.0%
o	4803	5.8%
t	4685	5.6%
r	4540	5.5%
n	4437	5.3%
i	4398	5.3%
s	4306	5.2%
l	2860	3.4%
Other values (82)	27646	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	83071	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	12738	15.3%
e	7675	9.2%
a	4983	6.0%
o	4803	5.8%
t	4685	5.6%
r	4540	5.5%
n	4437	5.3%
i	4398	5.3%
s	4306	5.2%
l	2860	3.4%
Other values (82)	27646	33.3%

Visibility
Real number (ℝ)

High correlation Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2071178.6

Minimum	582886
Maximum	22572066
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	582886
5-th percentile	621386.7
Q1	799717
median	1215990
Q3	2304652
95-th percentile	6645731.1
Maximum	22572066
Range	21989180
Interquartile range (IQR)	1504935

Descriptive statistics

Standard deviation	2399035.7
Coefficient of variation (CV)	1.1582949
Kurtosis	19.576633
Mean	2071178.6
Median Absolute Deviation (MAD)	501087
Skewness	3.7796256
Sum	2.0691074 × 10⁹
Variance	5.7553721 × 10¹²
Monotonicity	Strictly decreasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
582886	1	0.1%
22572066	1	0.1%
21331409	1	0.1%
19344936	1	0.1%
18797641	1	0.1%
16353543	1	0.1%
15318643	1	0.1%
596558	1	0.1%
596772	1	0.1%
597265	1	0.1%
Other values (989)	989	99.0%

Value	Count	Frequency (%)
582886	1	0.1%
583765	1	0.1%
585267	1	0.1%
585417	1	0.1%
585428	1	0.1%
586529	1	0.1%
587557	1	0.1%
588887	1	0.1%
589230	1	0.1%
590578	1	0.1%

Value	Count	Frequency (%)
22572066	1	0.1%
21331409	1	0.1%
19344936	1	0.1%
18797641	1	0.1%
16353543	1	0.1%
15318643	1	0.1%
14627061	1	0.1%
13507301	1	0.1%
13339952	1	0.1%
13255807	1	0.1%

Cleaned_Headline
Text

Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	178.8 KiB

Length

Max length	263
Median length	142
Mean length	82.844845
Min length	20

Characters and Unicode

Total characters	82762
Distinct characters	92
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	999 ?
Unique (%)	100.0%

Sample

1st row	Ford is forced to immediately shut down factories and halt car production as CEO admits 'day to day' struggle for brand
2nd row	New U.S. Driving License Rule for Seniors Begins July 2025 - Essential Changes for Drivers Aged 70 and Above
3rd row	Cadets who met all Air Force Academy graduation standards denied commissions because they’re transgender
4th row	The DMV confirms it - The United States is ending the benefit that allowed drivers to drive with an expired license without immediate renewal - millions of drivers will have to renew urgently
5th row	McDonald's Removing 1 Breakfast Menu Item for Good on July 2

Value	Count	Frequency (%)
to	419	3.1%
the	373	2.7%
in	274	2.0%
of	209	1.5%
a	197	1.4%
for	194	1.4%
and	193	1.4%
new	143	1.0%
with	104	0.8%
is	98	0.7%
Other values (4231)	11491	83.9%

Most occurring characters

Value	Count	Frequency (%)
	12696	15.3%
e	7648	9.2%
a	4964	6.0%
o	4801	5.8%
t	4674	5.6%
r	4525	5.5%
n	4428	5.4%
i	4386	5.3%
s	4294	5.2%
l	2854	3.4%
Other values (82)	27492	33.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	82762	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	12696	15.3%
e	7648	9.2%
a	4964	6.0%
o	4801	5.8%
t	4674	5.6%
r	4525	5.5%
n	4428	5.4%
i	4386	5.3%
s	4294	5.2%
l	2854	3.4%
Other values (82)	27492	33.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	82762	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	12696	15.3%
e	7648	9.2%
a	4964	6.0%
o	4801	5.8%
t	4674	5.6%
r	4525	5.5%
n	4428	5.4%
i	4386	5.3%
s	4294	5.2%
l	2854	3.4%
Other values (82)	27492	33.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	82762	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	12696	15.3%
e	7648	9.2%
a	4964	6.0%
o	4801	5.8%
t	4674	5.6%
r	4525	5.5%
n	4428	5.4%
i	4386	5.3%
s	4294	5.2%
l	2854	3.4%
Other values (82)	27492	33.2%

Main_Category
Categorical

High correlation

Distinct	15
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	73.1 KiB

News_and_Current_Events	246
Finance_and_Business	176
Entertainment_and_Culture	97
Gastronomy	91
Science	72
Other values (10)	317

Length

Max length	26
Median length	23
Mean length	17.836837
Min length	6

Characters and Unicode

Total characters	17819
Distinct characters	35
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	Finance_and_Business
2nd row	News_and_Current_Events
3rd row	News_and_Current_Events
4th row	News_and_Current_Events
5th row	Gastronomy

Common Values

Value	Count	Frequency (%)
News_and_Current_Events	246	24.6%
Finance_and_Business	176	17.6%
Entertainment_and_Culture	97	9.7%
Gastronomy	91	9.1%
Science	72	7.2%
Health_and_Wellness	59	5.9%
Home_and_Lifestyle	52	5.2%
Travel	48	4.8%
Curiosities_and_Miscellany	43	4.3%
Public_Safety	41	4.1%
Other values (5)	74	7.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
news_and_current_events	246	24.6%
finance_and_business	176	17.6%
entertainment_and_culture	97	9.7%
gastronomy	91	9.1%
science	72	7.2%
health_and_wellness	59	5.9%
home_and_lifestyle	52	5.2%
travel	48	4.8%
curiosities_and_miscellany	43	4.3%
public_safety	41	4.1%
Other values (5)	74	7.4%

Most occurring characters

Value	Count	Frequency (%)
n	2308	13.0%
e	2066	11.6%
_	1679	9.4%
s	1474	8.3%
a	1279	7.2%
t	1227	6.9%
r	905	5.1%
i	836	4.7%
u	747	4.2%
d	742	4.2%
Other values (25)	4556	25.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	17819	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	2308	13.0%
e	2066	11.6%
_	1679	9.4%
s	1474	8.3%
a	1279	7.2%
t	1227	6.9%
r	905	5.1%
i	836	4.7%
u	747	4.2%
d	742	4.2%
Other values (25)	4556	25.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	17819	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	2308	13.0%
e	2066	11.6%
_	1679	9.4%
s	1474	8.3%
a	1279	7.2%
t	1227	6.9%
r	905	5.1%
i	836	4.7%
u	747	4.2%
d	742	4.2%
Other values (25)	4556	25.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	17819	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	2308	13.0%
e	2066	11.6%
_	1679	9.4%
s	1474	8.3%
a	1279	7.2%
t	1227	6.9%
r	905	5.1%
i	836	4.7%
u	747	4.2%
d	742	4.2%
Other values (25)	4556	25.6%

Subcategory_1
Text

Distinct	117
Distinct (%)	11.7%
Missing	0
Missing (%)	0.0%
Memory size	71.5 KiB

Length

Max length	30
Median length	23
Mean length	16.166166
Min length	3

Characters and Unicode

Total characters	16150
Distinct characters	51
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	46 ?
Unique (%)	4.6%

Sample

1st row	Companies & Entrepreneurship
2nd row	Politics
3rd row	Politics
4th row	Politics
5th row	Restaurants & Chefs

Value	Count	Frequency (%)
	359	18.6%
companies	68	3.5%
entrepreneurship	68	3.5%
politics	57	3.0%
celebrities	57	3.0%
influencers	57	3.0%
crime	56	2.9%
judicial	56	2.9%
recipes	55	2.8%
international	46	2.4%
Other values (147)	1051	54.5%

Most occurring characters

Value	Count	Frequency (%)
e	1708	10.6%
i	1509	9.3%
n	1440	8.9%
s	1107	6.9%
r	1086	6.7%
t	1009	6.2%
a	952	5.9%
	931	5.8%
o	754	4.7%
l	661	4.1%
Other values (41)	4993	30.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	16150	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1708	10.6%
i	1509	9.3%
n	1440	8.9%
s	1107	6.9%
r	1086	6.7%
t	1009	6.2%
a	952	5.9%
	931	5.8%
o	754	4.7%
l	661	4.1%
Other values (41)	4993	30.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	16150	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1708	10.6%
i	1509	9.3%
n	1440	8.9%
s	1107	6.9%
r	1086	6.7%
t	1009	6.2%
a	952	5.9%
	931	5.8%
o	754	4.7%
l	661	4.1%
Other values (41)	4993	30.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	16150	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1708	10.6%
i	1509	9.3%
n	1440	8.9%
s	1107	6.9%
r	1086	6.7%
t	1009	6.2%
a	952	5.9%
	931	5.8%
o	754	4.7%
l	661	4.1%
Other values (41)	4993	30.9%

Subcategory_2
Text

Distinct	108
Distinct (%)	10.8%
Missing	0
Missing (%)	0.0%
Memory size	61.0 KiB

Length

Max length	30
Median length	3
Mean length	5.4314314
Min length	3

Characters and Unicode

Total characters	5426
Distinct characters	51
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	83 ?
Unique (%)	8.3%

Sample

1st row	N/A
2nd row	Government
3rd row	Government
4th row	Government
5th row	N/A

Value	Count	Frequency (%)
n/a	669	60.7%
government	44	4.0%
tips	32	2.9%
advances	22	2.0%
main	21	1.9%
courses	21	1.9%
national	20	1.8%
desserts	20	1.8%
	19	1.7%
prevention	14	1.3%
Other values (130)	221	20.0%

Most occurring characters

Value	Count	Frequency (%)
A	717	13.2%
N	693	12.8%
/	671	12.4%
e	423	7.8%
s	335	6.2%
n	296	5.5%
i	275	5.1%
t	214	3.9%
r	199	3.7%
a	195	3.6%
Other values (41)	1408	25.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5426	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	717	13.2%
N	693	12.8%
/	671	12.4%
e	423	7.8%
s	335	6.2%
n	296	5.5%
i	275	5.1%
t	214	3.9%
r	199	3.7%
a	195	3.6%
Other values (41)	1408	25.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5426	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	717	13.2%
N	693	12.8%
/	671	12.4%
e	423	7.8%
s	335	6.2%
n	296	5.5%
i	275	5.1%
t	214	3.9%
r	199	3.7%
a	195	3.6%
Other values (41)	1408	25.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5426	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	717	13.2%
N	693	12.8%
/	671	12.4%
e	423	7.8%
s	335	6.2%
n	296	5.5%
i	275	5.1%
t	214	3.9%
r	199	3.7%
a	195	3.6%
Other values (41)	1408	25.9%

Clarity_and_Conciseness_Value
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	59.7 KiB

High	970
Medium	25
Low	4

Length

Max length	6
Median length	4
Mean length	4.046046
Min length	3

Characters and Unicode

Total characters	4042
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High
2nd row	High
3rd row	High
4th row	High
5th row	High

Common Values

Value	Count	Frequency (%)
High	970	97.1%
Medium	25	2.5%
Low	4	0.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	970	97.1%
medium	25	2.5%
low	4	0.4%

Most occurring characters

Value	Count	Frequency (%)
i	995	24.6%
H	970	24.0%
g	970	24.0%
h	970	24.0%
M	25	0.6%
e	25	0.6%
d	25	0.6%
u	25	0.6%
m	25	0.6%
L	4	0.1%
Other values (2)	8	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4042	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	995	24.6%
H	970	24.0%
g	970	24.0%
h	970	24.0%
M	25	0.6%
e	25	0.6%
d	25	0.6%
u	25	0.6%
m	25	0.6%
L	4	0.1%
Other values (2)	8	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4042	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	995	24.6%
H	970	24.0%
g	970	24.0%
h	970	24.0%
M	25	0.6%
e	25	0.6%
d	25	0.6%
u	25	0.6%
m	25	0.6%
L	4	0.1%
Other values (2)	8	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4042	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	995	24.6%
H	970	24.0%
g	970	24.0%
h	970	24.0%
M	25	0.6%
e	25	0.6%
d	25	0.6%
u	25	0.6%
m	25	0.6%
L	4	0.1%
Other values (2)	8	0.2%

Clarity_and_Conciseness_Comment
Text

Distinct	875
Distinct (%)	87.6%
Missing	0
Missing (%)	0.0%
Memory size	145.6 KiB

Length

Max length	205
Median length	144
Mean length	91.099099
Min length	30

Characters and Unicode

Total characters	91008
Distinct characters	78
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	851 ?
Unique (%)	85.2%

Sample

1st row	The main message is very clear and easy to understand, detailing Ford's production halt and the CEO's admission of struggle.
2nd row	The main message is exceptionally clear, detailing who, what, and when without ambiguity.
3rd row	The main message is very clear and direct, stating precisely what occurred and why.
4th row	The main message is very clear and direct, stating the change, its source, and its impact.
5th row	The message is clear and to the point, identifying the brand, action, and date.

Value	Count	Frequency (%)
the	1733	11.8%
and	1197	8.1%
is	886	6.0%
message	619	4.2%
clear	599	4.1%
to	579	3.9%
main	577	3.9%
easy	491	3.3%
understand	475	3.2%
headline	363	2.5%
Other values (1677)	7170	48.8%

Most occurring characters

Value	Count	Frequency (%)
	13690	15.0%
e	10113	11.1%
a	7677	8.4%
t	6157	6.8%
n	6012	6.6%
s	5955	6.5%
i	5804	6.4%
r	3949	4.3%
d	3824	4.2%
c	3192	3.5%
Other values (68)	24635	27.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	91008	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	13690	15.0%
e	10113	11.1%
a	7677	8.4%
t	6157	6.8%
n	6012	6.6%
s	5955	6.5%
i	5804	6.4%
r	3949	4.3%
d	3824	4.2%
c	3192	3.5%
Other values (68)	24635	27.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	91008	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	13690	15.0%
e	10113	11.1%
a	7677	8.4%
t	6157	6.8%
n	6012	6.6%
s	5955	6.5%
i	5804	6.4%
r	3949	4.3%
d	3824	4.2%
c	3192	3.5%
Other values (68)	24635	27.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	91008	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	13690	15.0%
e	10113	11.1%
a	7677	8.4%
t	6157	6.8%
n	6012	6.6%
s	5955	6.5%
i	5804	6.4%
r	3949	4.3%
d	3824	4.2%
c	3192	3.5%
Other values (68)	24635	27.1%

Relevance_and_Timeliness_Value
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	59.7 KiB

High	952
Medium	47

Length

Max length	6
Median length	4
Mean length	4.0940941
Min length	4

Characters and Unicode

Total characters	4090
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High
2nd row	High
3rd row	High
4th row	High
5th row	High

Common Values

Value	Count	Frequency (%)
High	952	95.3%
Medium	47	4.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	952	95.3%
medium	47	4.7%

Most occurring characters

Value	Count	Frequency (%)
i	999	24.4%
H	952	23.3%
g	952	23.3%
h	952	23.3%
M	47	1.1%
e	47	1.1%
d	47	1.1%
u	47	1.1%
m	47	1.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4090	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	999	24.4%
H	952	23.3%
g	952	23.3%
h	952	23.3%
M	47	1.1%
e	47	1.1%
d	47	1.1%
u	47	1.1%
m	47	1.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4090	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	999	24.4%
H	952	23.3%
g	952	23.3%
h	952	23.3%
M	47	1.1%
e	47	1.1%
d	47	1.1%
u	47	1.1%
m	47	1.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4090	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	999	24.4%
H	952	23.3%
g	952	23.3%
h	952	23.3%
M	47	1.1%
e	47	1.1%
d	47	1.1%
u	47	1.1%
m	47	1.1%

Relevance_and_Timeliness_Comment
Text

Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	167.0 KiB

Length

Max length	243
Median length	163
Mean length	113.58959
Min length	45

Characters and Unicode

Total characters	113476
Distinct characters	76
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	999 ?
Unique (%)	100.0%

Sample

1st row	The headline discusses a significant event for a major global brand, which is highly relevant and timely for business and general news audiences.
2nd row	Highly relevant to a specific, large demographic (seniors/drivers) and provides timely information about a future change.
3rd row	The topic of transgender rights and military policy is highly current and relevant, resonating with ongoing social and political discussions.
4th row	Highly relevant as it affects a large demographic ('millions of drivers') and requires urgent action, indicating timeliness.
5th row	Highly relevant for McDonald's customers and tied to a specific future date, July 2.

Value	Count	Frequency (%)
and	1193	7.1%
a	651	3.9%
relevant	577	3.4%
of	484	2.9%
the	470	2.8%
to	458	2.7%
highly	443	2.6%
are	390	2.3%
interest	386	2.3%
is	365	2.2%
Other values (2012)	11347	67.7%

Most occurring characters

Value	Count	Frequency (%)
	15765	13.9%
e	12624	11.1%
i	8288	7.3%
n	8274	7.3%
a	7902	7.0%
t	7401	6.5%
r	6228	5.5%
s	5874	5.2%
o	5324	4.7%
l	4946	4.4%
Other values (66)	30850	27.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	113476	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	15765	13.9%
e	12624	11.1%
i	8288	7.3%
n	8274	7.3%
a	7902	7.0%
t	7401	6.5%
r	6228	5.5%
s	5874	5.2%
o	5324	4.7%
l	4946	4.4%
Other values (66)	30850	27.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	113476	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	15765	13.9%
e	12624	11.1%
i	8288	7.3%
n	8274	7.3%
a	7902	7.0%
t	7401	6.5%
r	6228	5.5%
s	5874	5.2%
o	5324	4.7%
l	4946	4.4%
Other values (66)	30850	27.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	113476	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	15765	13.9%
e	12624	11.1%
i	8288	7.3%
n	8274	7.3%
a	7902	7.0%
t	7401	6.5%
r	6228	5.5%
s	5874	5.2%
o	5324	4.7%
l	4946	4.4%
Other values (66)	30850	27.2%

Strategic_Keyword_Usage_Value
Categorical

High correlation Imbalance

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	59.7 KiB

High	966
Medium	32
Low	1

Length

Max length	6
Median length	4
Mean length	4.0630631
Min length	3

Characters and Unicode

Total characters	4059
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	High
2nd row	High
3rd row	High
4th row	High
5th row	High

Common Values

Value	Count	Frequency (%)
High	966	96.7%
Medium	32	3.2%
Low	1	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
high	966	96.7%
medium	32	3.2%
low	1	0.1%

Most occurring characters

Value	Count	Frequency (%)
i	998	24.6%
H	966	23.8%
g	966	23.8%
h	966	23.8%
M	32	0.8%
e	32	0.8%
d	32	0.8%
u	32	0.8%
m	32	0.8%
L	1	< 0.1%
Other values (2)	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4059	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	998	24.6%
H	966	23.8%
g	966	23.8%
h	966	23.8%
M	32	0.8%
e	32	0.8%
d	32	0.8%
u	32	0.8%
m	32	0.8%
L	1	< 0.1%
Other values (2)	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4059	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	998	24.6%
H	966	23.8%
g	966	23.8%
h	966	23.8%
M	32	0.8%
e	32	0.8%
d	32	0.8%
u	32	0.8%
m	32	0.8%
L	1	< 0.1%
Other values (2)	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4059	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	998	24.6%
H	966	23.8%
g	966	23.8%
h	966	23.8%
M	32	0.8%
e	32	0.8%
d	32	0.8%
u	32	0.8%
m	32	0.8%
L	1	< 0.1%
Other values (2)	2	< 0.1%

Strategic_Keyword_Usage_Comment
Text

Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	188.3 KiB

Length

Max length	241
Median length	179
Mean length	128.59059
Min length	43

Characters and Unicode

Total characters	128462
Distinct characters	82
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	999 ?
Unique (%)	100.0%

Sample

1st row	Key terms like 'Ford', 'factories', 'car production', 'CEO', and 'struggle' are used effectively, making the headline highly discoverable and appealing.
2nd row	Contains highly relevant keywords like 'U.S. Driving License Rule', 'Seniors', 'July 2025', 'Essential Changes', and 'Drivers Aged 70 and Above'.
3rd row	Uses strong, specific keywords like 'Cadets', 'Air Force Academy', 'denied commissions', and 'transgender', which are highly relevant to the subject matter and discoverable.
4th row	Uses strong keywords like 'DMV', 'United States', 'expired license', 'drivers', and 'renew urgently', which are highly searchable and relevant.
5th row	Uses strong keywords like 'McDonald's', 'Breakfast Menu', and 'Removing', appealing to target audience interests.

Value	Count	Frequency (%)
and	1576	8.7%
keywords	828	4.6%
like	797	4.4%
are	740	4.1%
relevant	735	4.0%
highly	593	3.3%
to	508	2.8%
uses	494	2.7%
the	422	2.3%
audience	312	1.7%
Other values (3142)	11163	61.4%

Most occurring characters

Value	Count	Frequency (%)
	17170	13.4%
e	13573	10.6%
a	8894	6.9%
r	7340	5.7%
t	6934	5.4%
n	6775	5.3%
i	6696	5.2%
s	6433	5.0%
l	5384	4.2%
o	5103	4.0%
Other values (72)	44160	34.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	128462	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	17170	13.4%
e	13573	10.6%
a	8894	6.9%
r	7340	5.7%
t	6934	5.4%
n	6775	5.3%
i	6696	5.2%
s	6433	5.0%
l	5384	4.2%
o	5103	4.0%
Other values (72)	44160	34.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	128462	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	17170	13.4%
e	13573	10.6%
a	8894	6.9%
r	7340	5.7%
t	6934	5.4%
n	6775	5.3%
i	6696	5.2%
s	6433	5.0%
l	5384	4.2%
o	5103	4.0%
Other values (72)	44160	34.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	128462	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	17170	13.4%
e	13573	10.6%
a	8894	6.9%
r	7340	5.7%
t	6934	5.4%
n	6775	5.3%
i	6696	5.2%
s	6433	5.0%
l	5384	4.2%
o	5103	4.0%
Other values (72)	44160	34.4%

Originality_and_Differentiation_Value
Categorical

High correlation

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	61.0 KiB

Medium	733
High	226
Low	40

Length

Max length	6
Median length	6
Mean length	5.4274274
Min length	3

Characters and Unicode

Total characters	5422
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Medium
2nd row	Medium
3rd row	Medium
4th row	Medium
5th row	Medium

Common Values

Value	Count	Frequency (%)
Medium	733	73.4%
High	226	22.6%
Low	40	4.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
medium	733	73.4%
high	226	22.6%
low	40	4.0%

Most occurring characters

Value	Count	Frequency (%)
i	959	17.7%
M	733	13.5%
e	733	13.5%
d	733	13.5%
u	733	13.5%
m	733	13.5%
H	226	4.2%
g	226	4.2%
h	226	4.2%
L	40	0.7%
Other values (2)	80	1.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5422	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	959	17.7%
M	733	13.5%
e	733	13.5%
d	733	13.5%
u	733	13.5%
m	733	13.5%
H	226	4.2%
g	226	4.2%
h	226	4.2%
L	40	0.7%
Other values (2)	80	1.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5422	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	959	17.7%
M	733	13.5%
e	733	13.5%
d	733	13.5%
u	733	13.5%
m	733	13.5%
H	226	4.2%
g	226	4.2%
h	226	4.2%
L	40	0.7%
Other values (2)	80	1.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5422	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	959	17.7%
M	733	13.5%
e	733	13.5%
d	733	13.5%
u	733	13.5%
m	733	13.5%
H	226	4.2%
g	226	4.2%
h	226	4.2%
L	40	0.7%
Other values (2)	80	1.5%

Originality_and_Differentiation_Comment
Text

Unique

Distinct	999
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	189.9 KiB

Length

Max length	255
Median length	178
Mean length	130.62262
Min length	45

Characters and Unicode

Total characters	130492
Distinct characters	88
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	999 ?
Unique (%)	100.0%

Sample

1st row	While the subject matter is impactful, the phrasing is a standard news report style, not particularly unique in its linguistic approach.
2nd row	While a standard news announcement format, the specific details make it distinct, yet it lacks a unique angle or creative phrasing.
3rd row	The specific event described is notable, though the broader subject of transgender individuals in the military has been discussed before. It offers a distinct event within a known debate.
4th row	While the specific policy change is unique, the headline structure (authority confirms X - consequence) is common. Its strength lies in the immediate, widespread impact.
5th row	While common for fast-food news, the specificity of '1 Breakfast Menu Item' and 'for Good' provides some differentiation.

Value	Count	Frequency (%)
the	1679	8.3%
a	1110	5.5%
and	725	3.6%
is	719	3.6%
of	562	2.8%
specific	556	2.8%
unique	548	2.7%
common	510	2.5%
while	491	2.4%
angle	347	1.7%
Other values (2601)	12957	64.1%

Most occurring characters

Value	Count	Frequency (%)
	19205	14.7%
e	12747	9.8%
i	10366	7.9%
n	8472	6.5%
t	8461	6.5%
a	8253	6.3%
o	6735	5.2%
s	6342	4.9%
r	5597	4.3%
c	4516	3.5%
Other values (78)	39798	30.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	130492	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	19205	14.7%
e	12747	9.8%
i	10366	7.9%
n	8472	6.5%
t	8461	6.5%
a	8253	6.3%
o	6735	5.2%
s	6342	4.9%
r	5597	4.3%
c	4516	3.5%
Other values (78)	39798	30.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	130492	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	19205	14.7%
e	12747	9.8%
i	10366	7.9%
n	8472	6.5%
t	8461	6.5%
a	8253	6.3%
o	6735	5.2%
s	6342	4.9%
r	5597	4.3%
c	4516	3.5%
Other values (78)	39798	30.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	130492	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	19205	14.7%
e	12747	9.8%
i	10366	7.9%
n	8472	6.5%
t	8461	6.5%
a	8253	6.3%
o	6735	5.2%
s	6342	4.9%
r	5597	4.3%
c	4516	3.5%
Other values (78)	39798	30.5%

Contains_Numbers
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

True	506
False	493

Value	Count	Frequency (%)
True	506	50.7%
False	493	49.3%

Contains_Quotes
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	855
True	144

Value	Count	Frequency (%)
False	855	85.6%
True	144	14.4%

Contains_Question_Mark
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	959
True	40

Value	Count	Frequency (%)
False	959	96.0%
True	40	4.0%

Contains_Colon
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	871
True	128

Value	Count	Frequency (%)
False	871	87.2%
True	128	12.8%

Contains_Hyphen
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	734
True	265

Value	Count	Frequency (%)
False	734	73.5%
True	265	26.5%

Contains_Exclamation_Mark
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	996
True	3

Value	Count	Frequency (%)
False	996	99.7%
True	3	0.3%

Starts_With_Number
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	912
True	87

Value	Count	Frequency (%)
False	912	91.3%
True	87	8.7%

Ends_With_Question_Mark
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	972
True	27

Value	Count	Frequency (%)
False	972	97.3%
True	27	2.7%

Length_General_Assessment
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	64.9 KiB

Adequate	929
Too long, risk of truncation	70

Length

Max length	28
Median length	8
Mean length	9.4014014
Min length	8

Characters and Unicode

Total characters	9392
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Adequate
2nd row	Adequate
3rd row	Adequate
4th row	Adequate
5th row	Adequate

Common Values

Value	Count	Frequency (%)
Adequate	929	93.0%
Too long, risk of truncation	70	7.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
adequate	929	72.6%
too	70	5.5%
long	70	5.5%
risk	70	5.5%
of	70	5.5%
truncation	70	5.5%

Most occurring characters

Value	Count	Frequency (%)
e	1858	19.8%
t	1069	11.4%
u	999	10.6%
a	999	10.6%
q	929	9.9%
d	929	9.9%
A	929	9.9%
o	350	3.7%
	280	3.0%
n	210	2.2%
Other values (10)	840	8.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	9392	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1858	19.8%
t	1069	11.4%
u	999	10.6%
a	999	10.6%
q	929	9.9%
d	929	9.9%
A	929	9.9%
o	350	3.7%
	280	3.0%
n	210	2.2%
Other values (10)	840	8.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	9392	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1858	19.8%
t	1069	11.4%
u	999	10.6%
a	999	10.6%
q	929	9.9%
d	929	9.9%
A	929	9.9%
o	350	3.7%
	280	3.0%
n	210	2.2%
Other values (10)	840	8.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	9392	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1858	19.8%
t	1069	11.4%
u	999	10.6%
a	999	10.6%
q	929	9.9%
d	929	9.9%
A	929	9.9%
o	350	3.7%
	280	3.0%
n	210	2.2%
Other values (10)	840	8.9%

Length_Number_of_Characters
Real number (ℝ)

High correlation

Distinct	135
Distinct (%)	13.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	76.751752

Minimum	19
Maximum	277
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	19
5-th percentile	42.9
Q1	58
median	70
Q3	90
95-th percentile	125
Maximum	277
Range	258
Interquartile range (IQR)	32

Descriptive statistics

Standard deviation	30.35885
Coefficient of variation (CV)	0.39554602
Kurtosis	7.9557975
Mean	76.751752
Median Absolute Deviation (MAD)	16
Skewness	2.1209404
Sum	76675
Variance	921.65975
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
59	45	4.5%
70	30	3.0%
60	29	2.9%
69	27	2.7%
58	26	2.6%
55	25	2.5%
75	25	2.5%
50	23	2.3%
104	22	2.2%
64	22	2.2%
Other values (125)	725	72.6%

Value	Count	Frequency (%)
19	1	0.1%
21	1	0.1%
25	1	0.1%
26	1	0.1%
28	1	0.1%
31	2	0.2%
32	1	0.1%
33	3	0.3%
34	2	0.2%
35	6	0.6%

Value	Count	Frequency (%)
277	1	0.1%
262	1	0.1%
255	1	0.1%
250	1	0.1%
228	1	0.1%
225	1	0.1%
219	1	0.1%
205	1	0.1%
201	1	0.1%
200	1	0.1%

Emphatic_Capitalization_Usage
Text

Distinct	59
Distinct (%)	5.9%
Missing	0
Missing (%)	0.0%
Memory size	61.0 KiB

Length

Max length	183
Median length	2
Mean length	5.3433433
Min length	2

Characters and Unicode

Total characters	5338
Distinct characters	66
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	58 ?
Unique (%)	5.8%

Sample

1st row	No
2nd row	No
3rd row	No
4th row	No
5th row	No

Value	Count	Frequency (%)
no	942	65.5%
yes	58	4.0%
justified	29	2.0%
use	29	2.0%
impact	29	2.0%
seeks	28	1.9%
the	11	0.8%
for	11	0.8%
and	8	0.6%
a	8	0.6%
Other values (230)	285	19.8%

Most occurring characters

Value	Count	Frequency (%)
o	1042	19.5%
N	953	17.9%
	439	8.2%
e	358	6.7%
s	266	5.0%
'	248	4.6%
i	211	4.0%
,	187	3.5%
t	156	2.9%
a	145	2.7%
Other values (56)	1333	25.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5338	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	1042	19.5%
N	953	17.9%
	439	8.2%
e	358	6.7%
s	266	5.0%
'	248	4.6%
i	211	4.0%
,	187	3.5%
t	156	2.9%
a	145	2.7%
Other values (56)	1333	25.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5338	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	1042	19.5%
N	953	17.9%
	439	8.2%
e	358	6.7%
s	266	5.0%
'	248	4.6%
i	211	4.0%
,	187	3.5%
t	156	2.9%
a	145	2.7%
Other values (56)	1333	25.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5338	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	1042	19.5%
N	953	17.9%
	439	8.2%
e	358	6.7%
s	266	5.0%
'	248	4.6%
i	211	4.0%
,	187	3.5%
t	156	2.9%
a	145	2.7%
Other values (56)	1333	25.0%

Main_Classification
Categorical

High correlation

Distinct	27
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	74.6 KiB

Declarative Simple	596
Mystery/Revelation	88
Attribution ('according to', 'reveals')	53
List/Numbered	41
Direct Question	38
Other values (22)	183

Length

Max length	52
Median length	18
Mean length	19.363363
Min length	4

Characters and Unicode

Total characters	19344
Distinct characters	43
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	8 ?
Unique (%)	0.8%

Sample

1st row	Declarative Simple
2nd row	Declarative Simple
3rd row	Declarative Simple
4th row	Urgency
5th row	Declarative Simple

Common Values

Value	Count	Frequency (%)
Declarative Simple	596	59.7%
Mystery/Revelation	88	8.8%
Attribution ('according to', 'reveals')	53	5.3%
List/Numbered	41	4.1%
Direct Question	38	3.8%
List/Numbered ('5 ways')	37	3.7%
Direct Quote	33	3.3%
Superlative ('best', 'worst')	23	2.3%
Mystery/Revelation ('secret', 'truth')	16	1.6%
Direct Quote/Attribution	14	1.4%
Other values (17)	60	6.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
declarative	597	29.4%
simple	596	29.4%
mystery/revelation	104	5.1%
direct	88	4.3%
list/numbered	81	4.0%
according	56	2.8%
attribution	56	2.8%
reveals	56	2.8%
to	56	2.8%
question	48	2.4%
Other values (23)	292	14.4%

Most occurring characters

Value	Count	Frequency (%)
e	2743	14.2%
i	1786	9.2%
a	1520	7.9%
t	1516	7.8%
l	1397	7.2%
r	1188	6.1%
	1031	5.3%
c	832	4.3%
v	814	4.2%
m	693	3.6%
Other values (33)	5824	30.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	19344	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	2743	14.2%
i	1786	9.2%
a	1520	7.9%
t	1516	7.8%
l	1397	7.2%
r	1188	6.1%
	1031	5.3%
c	832	4.3%
v	814	4.2%
m	693	3.6%
Other values (33)	5824	30.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	19344	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	2743	14.2%
i	1786	9.2%
a	1520	7.9%
t	1516	7.8%
l	1397	7.2%
r	1188	6.1%
	1031	5.3%
c	832	4.3%
v	814	4.2%
m	693	3.6%
Other values (33)	5824	30.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	19344	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	2743	14.2%
i	1786	9.2%
a	1520	7.9%
t	1516	7.8%
l	1397	7.2%
r	1188	6.1%
	1031	5.3%
c	832	4.3%
v	814	4.2%
m	693	3.6%
Other values (33)	5824	30.1%

Comment_Type_Justification
Text

Distinct	996
Distinct (%)	99.7%
Missing	0
Missing (%)	0.0%
Memory size	184.3 KiB

Length

Max length	333
Median length	173
Mean length	127.33433
Min length	46

Characters and Unicode

Total characters	127207
Distinct characters	84
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	994 ?
Unique (%)	99.5%

Sample

1st row	The headline presents a series of factual statements about Ford's situation and the CEO's admission without posing a question, using urgency markers, or comparing elements.
2nd row	The headline directly states a new rule and its implications, serving as a straightforward announcement.
3rd row	The headline makes a direct statement about an event, presenting it as a fact without using a question, direct quote, or emphasizing urgency.
4th row	The headline clearly states a new policy confirmed by an authority and strongly emphasizes the immediate, widespread need for action, particularly with the phrase 'renew urgently' affecting 'millions of drivers'.
5th row	The headline directly states a fact without posing a question, using a quote, or indicating urgency beyond the date.

Value	Count	Frequency (%)
a	1892	9.8%
the	1565	8.1%
headline	946	4.9%
or	597	3.1%
without	475	2.5%
and	388	2.0%
question	380	2.0%
statement	380	2.0%
about	347	1.8%
an	339	1.8%
Other values (1742)	11953	62.1%

Most occurring characters

Value	Count	Frequency (%)
	18263	14.4%
e	12967	10.2%
t	10875	8.5%
a	9448	7.4%
i	9257	7.3%
n	8132	6.4%
s	6605	5.2%
o	6184	4.9%
r	5812	4.6%
h	4195	3.3%
Other values (74)	35469	27.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	127207	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	18263	14.4%
e	12967	10.2%
t	10875	8.5%
a	9448	7.4%
i	9257	7.3%
n	8132	6.4%
s	6605	5.2%
o	6184	4.9%
r	5812	4.6%
h	4195	3.3%
Other values (74)	35469	27.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	127207	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	18263	14.4%
e	12967	10.2%
t	10875	8.5%
a	9448	7.4%
i	9257	7.3%
n	8132	6.4%
s	6605	5.2%
o	6184	4.9%
r	5812	4.6%
h	4195	3.3%
Other values (74)	35469	27.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	127207	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	18263	14.4%
e	12967	10.2%
t	10875	8.5%
a	9448	7.4%
i	9257	7.3%
n	8132	6.4%
s	6605	5.2%
o	6184	4.9%
r	5812	4.6%
h	4195	3.3%
Other values (74)	35469	27.9%

Temporal_Urgency_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	859
True	140

Value	Count	Frequency (%)
False	859	86.0%
True	140	14.0%

Temporal_Urgency_Words
Text

Distinct	100
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Memory size	59.4 KiB

Length

Max length	34
Median length	2
Mean length	3.6746747
Min length	2

Characters and Unicode

Total characters	3671
Distinct characters	60
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	79 ?
Unique (%)	7.9%

Sample

1st row	["immediately"]
2nd row	["Begins July 2025"]
3rd row	[]
4th row	["immediate","urgently"]
5th row	[]

Value	Count	Frequency (%)
	859	79.9%
this	11	1.0%
now	9	0.8%
july	8	0.7%
just	8	0.7%
tonight	7	0.7%
immediately	6	0.6%
1	6	0.6%
week	6	0.6%
new	6	0.6%
Other values (102)	149	13.9%

Most occurring characters

Value	Count	Frequency (%)
[	999	27.2%
]	999	27.2%
"	332	9.0%
e	157	4.3%
n	93	2.5%
t	91	2.5%
a	78	2.1%
	76	2.1%
i	73	2.0%
o	60	1.6%
Other values (50)	713	19.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3671	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	999	27.2%
]	999	27.2%
"	332	9.0%
e	157	4.3%
n	93	2.5%
t	91	2.5%
a	78	2.1%
	76	2.1%
i	73	2.0%
o	60	1.6%
Other values (50)	713	19.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3671	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	999	27.2%
]	999	27.2%
"	332	9.0%
e	157	4.3%
n	93	2.5%
t	91	2.5%
a	78	2.1%
	76	2.1%
i	73	2.0%
o	60	1.6%
Other values (50)	713	19.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3671	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	999	27.2%
]	999	27.2%
"	332	9.0%
e	157	4.3%
n	93	2.5%
t	91	2.5%
a	78	2.1%
	76	2.1%
i	73	2.0%
o	60	1.6%
Other values (50)	713	19.4%

Exclusivity_Present
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	962
True	37

Value	Count	Frequency (%)
False	962	96.3%
True	37	3.7%

Exclusivity_Words
Categorical

High correlation Imbalance

Distinct	30
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	58.1 KiB

[]	962
["Rare"]	3
["first"]	2
["only"]	2
["Exclusive"]	2
Other values (25)	28

Length

Max length	35
Median length	2
Mean length	2.4314314
Min length	2

Characters and Unicode

Total characters	2429
Distinct characters	46
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	22 ?
Unique (%)	2.2%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Common Values

Value	Count	Frequency (%)
[]	962	96.3%
["Rare"]	3	0.3%
["first"]	2	0.2%
["only"]	2	0.2%
["Exclusive"]	2	0.2%
["Limited-Edition"]	2	0.2%
["First"]	2	0.2%
["Only"]	2	0.2%
["Low-Key"]	1	0.1%
["one group"]	1	0.1%
Other values (20)	20	2.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	962	94.7%
first	6	0.6%
only	5	0.5%
rare	4	0.4%
exclusive	3	0.3%
limited-edition	2	0.2%
unique	2	0.2%
low-key	1	0.1%
one	1	0.1%
this	1	0.1%
Other values (29)	29	2.9%

Most occurring characters

Value	Count	Frequency (%)
[	999	41.1%
]	999	41.1%
"	82	3.4%
e	47	1.9%
i	32	1.3%
t	24	1.0%
n	23	0.9%
r	22	0.9%
s	18	0.7%
	17	0.7%
Other values (36)	166	6.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2429	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	999	41.1%
]	999	41.1%
"	82	3.4%
e	47	1.9%
i	32	1.3%
t	24	1.0%
n	23	0.9%
r	22	0.9%
s	18	0.7%
	17	0.7%
Other values (36)	166	6.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2429	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	999	41.1%
]	999	41.1%
"	82	3.4%
e	47	1.9%
i	32	1.3%
t	24	1.0%
n	23	0.9%
r	22	0.9%
s	18	0.7%
	17	0.7%
Other values (36)	166	6.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2429	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	999	41.1%
]	999	41.1%
"	82	3.4%
e	47	1.9%
i	32	1.3%
t	24	1.0%
n	23	0.9%
r	22	0.9%
s	18	0.7%
	17	0.7%
Other values (36)	166	6.8%

Authority_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	743
True	256

Value	Count	Frequency (%)
False	743	74.4%
True	256	25.6%

Authority_Words
Text

Distinct	216
Distinct (%)	21.6%
Missing	0
Missing (%)	0.0%
Memory size	61.5 KiB

Length

Max length	55
Median length	2
Mean length	5.9289289
Min length	2

Characters and Unicode

Total characters	5923
Distinct characters	58
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	191 ?
Unique (%)	19.1%

Sample

1st row	["CEO admits"]
2nd row	[]
3rd row	[]
4th row	["DMV","confirms"]
5th row	[]

Value	Count	Frequency (%)
	743	66.3%
experts	11	1.0%
social	7	0.6%
to	6	0.5%
scientists	6	0.5%
law	6	0.5%
tsa	6	0.5%
u.s	5	0.4%
security	5	0.4%
officials	5	0.4%
Other values (262)	320	28.6%

Most occurring characters

Value	Count	Frequency (%)
[	999	16.9%
]	999	16.9%
"	716	12.1%
e	285	4.8%
s	219	3.7%
r	214	3.6%
i	214	3.6%
o	211	3.6%
a	200	3.4%
t	185	3.1%
Other values (48)	1681	28.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5923	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	999	16.9%
]	999	16.9%
"	716	12.1%
e	285	4.8%
s	219	3.7%
r	214	3.6%
i	214	3.6%
o	211	3.6%
a	200	3.4%
t	185	3.1%
Other values (48)	1681	28.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5923	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	999	16.9%
]	999	16.9%
"	716	12.1%
e	285	4.8%
s	219	3.7%
r	214	3.6%
i	214	3.6%
o	211	3.6%
a	200	3.4%
t	185	3.1%
Other values (48)	1681	28.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5923	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	999	16.9%
]	999	16.9%
"	716	12.1%
e	285	4.8%
s	219	3.7%
r	214	3.6%
i	214	3.6%
o	211	3.6%
a	200	3.4%
t	185	3.1%
Other values (48)	1681	28.4%

Solution_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	833
True	166

Value	Count	Frequency (%)
False	833	83.4%
True	166	16.6%

Solution_Words
Text

Distinct	150
Distinct (%)	15.0%
Missing	0
Missing (%)	0.0%
Memory size	60.0 KiB

Length

Max length	44
Median length	2
Mean length	4.3493493
Min length	2

Characters and Unicode

Total characters	4345
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	137 ?
Unique (%)	13.7%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Value	Count	Frequency (%)
	834	74.3%
to	24	2.1%
how	18	1.6%
best	8	0.7%
way	5	0.4%
watch	4	0.4%
clean	4	0.4%
easy	4	0.4%
restored	3	0.3%
new	3	0.3%
Other values (188)	215	19.2%

Most occurring characters

Value	Count	Frequency (%)
[	999	23.0%
]	999	23.0%
"	434	10.0%
e	238	5.5%
o	145	3.3%
t	138	3.2%
	123	2.8%
i	100	2.3%
r	96	2.2%
a	92	2.1%
Other values (46)	981	22.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4345	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	999	23.0%
]	999	23.0%
"	434	10.0%
e	238	5.5%
o	145	3.3%
t	138	3.2%
	123	2.8%
i	100	2.3%
r	96	2.2%
a	92	2.1%
Other values (46)	981	22.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4345	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	999	23.0%
]	999	23.0%
"	434	10.0%
e	238	5.5%
o	145	3.3%
t	138	3.2%
	123	2.8%
i	100	2.3%
r	96	2.2%
a	92	2.1%
Other values (46)	981	22.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4345	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	999	23.0%
]	999	23.0%
"	434	10.0%
e	238	5.5%
o	145	3.3%
t	138	3.2%
	123	2.8%
i	100	2.3%
r	96	2.2%
a	92	2.1%
Other values (46)	981	22.6%

Economic_Benefit_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	850
True	149

Value	Count	Frequency (%)
False	850	85.1%
True	149	14.9%

Economic_Benefit_Words
Text

Distinct	141
Distinct (%)	14.1%
Missing	0
Missing (%)	0.0%
Memory size	60.5 KiB

Length

Max length	59
Median length	2
Mean length	4.7347347
Min length	2

Characters and Unicode

Total characters	4730
Distinct characters	70
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	131 ?
Unique (%)	13.1%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[]
5th row	[]

Value	Count	Frequency (%)
	850	76.8%
million	17	1.5%
refunds	4	0.4%
tax	4	0.4%
benefits	4	0.4%
tree	3	0.3%
valuable	3	0.3%
1	3	0.3%
billion	3	0.3%
free	3	0.3%
Other values (193)	213	19.2%

Most occurring characters

Value	Count	Frequency (%)
[	999	21.1%
]	999	21.1%
"	490	10.4%
e	183	3.9%
i	154	3.3%
l	152	3.2%
n	138	2.9%
,	119	2.5%
o	118	2.5%
	108	2.3%
Other values (60)	1270	26.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4730	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	999	21.1%
]	999	21.1%
"	490	10.4%
e	183	3.9%
i	154	3.3%
l	152	3.2%
n	138	2.9%
,	119	2.5%
o	118	2.5%
	108	2.3%
Other values (60)	1270	26.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4730	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	999	21.1%
]	999	21.1%
"	490	10.4%
e	183	3.9%
i	154	3.3%
l	152	3.2%
n	138	2.9%
,	119	2.5%
o	118	2.5%
	108	2.3%
Other values (60)	1270	26.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4730	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	999	21.1%
]	999	21.1%
"	490	10.4%
e	183	3.9%
i	154	3.3%
l	152	3.2%
n	138	2.9%
,	119	2.5%
o	118	2.5%
	108	2.3%
Other values (60)	1270	26.8%

Prohibition_Restriction_Present
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	926
True	73

Value	Count	Frequency (%)
False	926	92.7%
True	73	7.3%

Prohibition_Restriction_Words
Text

Distinct	65
Distinct (%)	6.5%
Missing	0
Missing (%)	0.0%
Memory size	58.9 KiB

Length

Max length	68
Median length	2
Mean length	3.2162162
Min length	2

Characters and Unicode

Total characters	3213
Distinct characters	50
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	57 ?
Unique (%)	5.7%

Sample

1st row	[]
2nd row	[]
3rd row	["denied"]
4th row	["ending the benefit","without immediate renewal"]
5th row	[]

Value	Count	Frequency (%)
	926	86.0%
to	9	0.8%
not	7	0.6%
avoid	5	0.5%
ban	4	0.4%
away	3	0.3%
banned	3	0.3%
banning	2	0.2%
neither","nor	2	0.2%
of	2	0.2%
Other values (103)	114	10.6%

Most occurring characters

Value	Count	Frequency (%)
[	999	31.1%
]	999	31.1%
"	192	6.0%
e	101	3.1%
o	82	2.6%
n	78	2.4%
	78	2.4%
i	74	2.3%
t	70	2.2%
r	53	1.6%
Other values (40)	487	15.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3213	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
[	999	31.1%
]	999	31.1%
"	192	6.0%
e	101	3.1%
o	82	2.6%
n	78	2.4%
	78	2.4%
i	74	2.3%
t	70	2.2%
r	53	1.6%
Other values (40)	487	15.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3213	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
[	999	31.1%
]	999	31.1%
"	192	6.0%
e	101	3.1%
o	82	2.6%
n	78	2.4%
	78	2.4%
i	74	2.3%
t	70	2.2%
r	53	1.6%
Other values (40)	487	15.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3213	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
[	999	31.1%
]	999	31.1%
"	192	6.0%
e	101	3.1%
o	82	2.6%
n	78	2.4%
	78	2.4%
i	74	2.3%
t	70	2.2%
r	53	1.6%
Other values (40)	487	15.2%

National_Relevance_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	603
True	396

Value	Count	Frequency (%)
False	603	60.4%
True	396	39.6%

National_Relevance_Words
Text

Distinct	237
Distinct (%)	23.7%
Missing	0
Missing (%)	0.0%
Memory size	64.3 KiB

Length

Max length	141
Median length	2
Mean length	8.7557558
Min length	2

Characters and Unicode

Total characters	8747
Distinct characters	60
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	199 ?
Unique (%)	19.9%

Sample

1st row	[]
2nd row	["U.S."]
3rd row	[]
4th row	["United States"]
5th row	[]

Value	Count	Frequency (%)
	603	50.4%
new	36	3.0%
york	34	2.8%
california	26	2.2%
states	22	1.8%
state	17	1.4%
texas	16	1.3%
us	15	1.3%
illinois	12	1.0%
u.s	11	0.9%
Other values (299)	405	33.8%

Most occurring characters

Value	Count	Frequency (%)
"	1312	15.0%
[	999	11.4%
]	999	11.4%
a	538	6.2%
e	395	4.5%
i	393	4.5%
n	344	3.9%
o	319	3.6%
t	311	3.6%
r	300	3.4%
Other values (50)	2837	32.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8747	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
"	1312	15.0%
[	999	11.4%
]	999	11.4%
a	538	6.2%
e	395	4.5%
i	393	4.5%
n	344	3.9%
o	319	3.6%
t	311	3.6%
r	300	3.4%
Other values (50)	2837	32.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8747	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
"	1312	15.0%
[	999	11.4%
]	999	11.4%
a	538	6.2%
e	395	4.5%
i	393	4.5%
n	344	3.9%
o	319	3.6%
t	311	3.6%
r	300	3.4%
Other values (50)	2837	32.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8747	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
"	1312	15.0%
[	999	11.4%
]	999	11.4%
a	538	6.2%
e	395	4.5%
i	393	4.5%
n	344	3.9%
o	319	3.6%
t	311	3.6%
r	300	3.4%
Other values (50)	2837	32.4%

Recognized_Brand_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	640
True	359

Value	Count	Frequency (%)
False	640	64.1%
True	359	35.9%

Recognized_Brand_Words
Text

Distinct	277
Distinct (%)	27.7%
Missing	0
Missing (%)	0.0%
Memory size	64.7 KiB

Length

Max length	154
Median length	2
Mean length	8.6286286
Min length	2

Characters and Unicode

Total characters	8620
Distinct characters	72
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	235 ?
Unique (%)	23.5%

Sample

1st row	["Ford"]
2nd row	[]
3rd row	[]
4th row	["DMV"]
5th row	["McDonald's"]

Value	Count	Frequency (%)
	642	48.9%
security	14	1.1%
walmart	13	1.0%
social	13	1.0%
air	9	0.7%
tsa	7	0.5%
tree	6	0.5%
dollar	6	0.5%
trump	6	0.5%
webb	6	0.5%
Other values (461)	592	45.1%

Most occurring characters

Value	Count	Frequency (%)
"	1106	12.8%
[	999	11.6%
]	999	11.6%
e	476	5.5%
a	421	4.9%
r	362	4.2%
	315	3.7%
i	309	3.6%
o	295	3.4%
l	263	3.1%
Other values (62)	3075	35.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8620	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
"	1106	12.8%
[	999	11.6%
]	999	11.6%
e	476	5.5%
a	421	4.9%
r	362	4.2%
	315	3.7%
i	309	3.6%
o	295	3.4%
l	263	3.1%
Other values (62)	3075	35.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8620	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
"	1106	12.8%
[	999	11.6%
]	999	11.6%
e	476	5.5%
a	421	4.9%
r	362	4.2%
	315	3.7%
i	309	3.6%
o	295	3.4%
l	263	3.1%
Other values (62)	3075	35.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8620	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
"	1106	12.8%
[	999	11.6%
]	999	11.6%
e	476	5.5%
a	421	4.9%
r	362	4.2%
	315	3.7%
i	309	3.6%
o	295	3.4%
l	263	3.1%
Other values (62)	3075	35.7%

Curiosity_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

True	785
False	214

Value	Count	Frequency (%)
True	785	78.6%
False	214	21.4%

Curiosity_Evidence
Text

Distinct	787
Distinct (%)	78.8%
Missing	0
Missing (%)	0.0%
Memory size	178.7 KiB

Length

Max length	273
Median length	204
Mean length	109.22022
Min length	0

Characters and Unicode

Total characters	109111
Distinct characters	86
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	786 ?
Unique (%)	78.7%

Sample

1st row
2nd row	The phrase 'Essential Changes' prompts readers to seek information on what those changes entail.
3rd row
4th row
5th row	The headline creates an information gap by not revealing which specific breakfast item is being removed.

Value	Count	Frequency (%)
the	1823	10.5%
and	590	3.4%
to	539	3.1%
an	499	2.9%
gap	497	2.9%
information	486	2.8%
creates	479	2.7%
about	398	2.3%
reader	342	2.0%
a	327	1.9%
Other values (2604)	11439	65.7%

Most occurring characters

Value	Count	Frequency (%)
	16633	15.2%
e	10759	9.9%
a	7903	7.2%
t	7440	6.8%
i	6769	6.2%
n	6352	5.8%
r	6117	5.6%
o	6082	5.6%
s	5413	5.0%
h	4311	4.0%
Other values (76)	31332	28.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	109111	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	16633	15.2%
e	10759	9.9%
a	7903	7.2%
t	7440	6.8%
i	6769	6.2%
n	6352	5.8%
r	6117	5.6%
o	6082	5.6%
s	5413	5.0%
h	4311	4.0%
Other values (76)	31332	28.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	109111	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	16633	15.2%
e	10759	9.9%
a	7903	7.2%
t	7440	6.8%
i	6769	6.2%
n	6352	5.8%
r	6117	5.6%
o	6082	5.6%
s	5413	5.0%
h	4311	4.0%
Other values (76)	31332	28.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	109111	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	16633	15.2%
e	10759	9.9%
a	7903	7.2%
t	7440	6.8%
i	6769	6.2%
n	6352	5.8%
r	6117	5.6%
o	6082	5.6%
s	5413	5.0%
h	4311	4.0%
Other values (76)	31332	28.7%

Fear_Concern_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	606
True	393

Value	Count	Frequency (%)
False	606	60.7%
True	393	39.3%

Fear_Concern_Evidence
Text

Distinct	395
Distinct (%)	39.5%
Missing	0
Missing (%)	0.0%
Memory size	109.5 KiB

Length

Max length	240
Median length	0
Mean length	50.398398
Min length	0

Characters and Unicode

Total characters	50348
Distinct characters	78
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	394 ?
Unique (%)	39.4%

Sample

1st row	The phrases 'forced to immediately shut down factories', 'halt car production', and 'struggle for brand' evoke concern about economic stability and the future of a major company.
2nd row
3rd row
4th row	The phrase 'millions of drivers will have to renew urgently' directly implies potential negative consequences or significant inconvenience if the reader fails to act, evoking concern.
5th row	The phrase 'Removing... for Good' could evoke concern among customers about a favorite item.

Value	Count	Frequency (%)
the	525	7.0%
and	358	4.8%
concern	327	4.4%
of	266	3.5%
a	215	2.9%
or	176	2.3%
about	163	2.2%
for	159	2.1%
potential	129	1.7%
evoke	126	1.7%
Other values (1665)	5064	67.4%

Most occurring characters

Value	Count	Frequency (%)
	7114	14.1%
e	5184	10.3%
n	3592	7.1%
o	3243	6.4%
a	3217	6.4%
i	2969	5.9%
t	2969	5.9%
r	2889	5.7%
s	2570	5.1%
c	2133	4.2%
Other values (68)	14468	28.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	50348	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	7114	14.1%
e	5184	10.3%
n	3592	7.1%
o	3243	6.4%
a	3217	6.4%
i	2969	5.9%
t	2969	5.9%
r	2889	5.7%
s	2570	5.1%
c	2133	4.2%
Other values (68)	14468	28.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	50348	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	7114	14.1%
e	5184	10.3%
n	3592	7.1%
o	3243	6.4%
a	3217	6.4%
i	2969	5.9%
t	2969	5.9%
r	2889	5.7%
s	2570	5.1%
c	2133	4.2%
Other values (68)	14468	28.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	50348	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	7114	14.1%
e	5184	10.3%
n	3592	7.1%
o	3243	6.4%
a	3217	6.4%
i	2969	5.9%
t	2969	5.9%
r	2889	5.7%
s	2570	5.1%
c	2133	4.2%
Other values (68)	14468	28.7%

Surprise_Awe_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	655
True	344

Value	Count	Frequency (%)
False	655	65.6%
True	344	34.4%

Surprise_Awe_Evidence
Text

Distinct	346
Distinct (%)	34.6%
Missing	0
Missing (%)	0.0%
Memory size	98.7 KiB

Length

Max length	206
Median length	0
Mean length	39.738739
Min length	0

Characters and Unicode

Total characters	39699
Distinct characters	79
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	345 ?
Unique (%)	34.5%

Sample

1st row
2nd row
3rd row
4th row
5th row

Value	Count	Frequency (%)
the	554	8.7%
of	371	5.8%
and	322	5.1%
a	303	4.8%
surprise	170	2.7%
unexpected	116	1.8%
is	108	1.7%
can	102	1.6%
surprising	98	1.5%
evoke	96	1.5%
Other values (1632)	4109	64.7%

Most occurring characters

Value	Count	Frequency (%)
	6004	15.1%
e	4332	10.9%
n	2534	6.4%
a	2492	6.3%
i	2435	6.1%
s	2356	5.9%
t	2149	5.4%
r	2058	5.2%
o	1993	5.0%
d	1143	2.9%
Other values (69)	12203	30.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	39699	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	6004	15.1%
e	4332	10.9%
n	2534	6.4%
a	2492	6.3%
i	2435	6.1%
s	2356	5.9%
t	2149	5.4%
r	2058	5.2%
o	1993	5.0%
d	1143	2.9%
Other values (69)	12203	30.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	39699	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	6004	15.1%
e	4332	10.9%
n	2534	6.4%
a	2492	6.3%
i	2435	6.1%
s	2356	5.9%
t	2149	5.4%
r	2058	5.2%
o	1993	5.0%
d	1143	2.9%
Other values (69)	12203	30.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	39699	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	6004	15.1%
e	4332	10.9%
n	2534	6.4%
a	2492	6.3%
i	2435	6.1%
s	2356	5.9%
t	2149	5.4%
r	2058	5.2%
o	1993	5.0%
d	1143	2.9%
Other values (69)	12203	30.7%

Indignation_Controversy_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	822
True	177

Value	Count	Frequency (%)
False	822	82.3%
True	177	17.7%

Indignation_Controversy_Evidence
Text

Distinct	179
Distinct (%)	17.9%
Missing	0
Missing (%)	0.0%
Memory size	83.6 KiB

Length

Max length	264
Median length	0
Mean length	24.13013
Min length	0

Characters and Unicode

Total characters	24106
Distinct characters	75
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	178 ?
Unique (%)	17.8%

Sample

1st row
2nd row
3rd row	The phrase 'denied commissions because they’re transgender' directly implies a potential act of discrimination, which is highly likely to provoke indignation and controversy among various audiences.
4th row
5th row

Value	Count	Frequency (%)
the	219	6.2%
and	168	4.7%
a	145	4.1%
indignation	122	3.4%
of	119	3.3%
or	91	2.6%
to	89	2.5%
provoke	86	2.4%
debate	77	2.2%
can	74	2.1%
Other values (1055)	2367	66.5%

Most occurring characters

Value	Count	Frequency (%)
	3379	14.0%
e	2185	9.1%
n	1867	7.7%
i	1799	7.5%
a	1693	7.0%
o	1680	7.0%
t	1556	6.5%
r	1276	5.3%
s	1103	4.6%
d	835	3.5%
Other values (65)	6733	27.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	24106	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	3379	14.0%
e	2185	9.1%
n	1867	7.7%
i	1799	7.5%
a	1693	7.0%
o	1680	7.0%
t	1556	6.5%
r	1276	5.3%
s	1103	4.6%
d	835	3.5%
Other values (65)	6733	27.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	24106	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	3379	14.0%
e	2185	9.1%
n	1867	7.7%
i	1799	7.5%
a	1693	7.0%
o	1680	7.0%
t	1556	6.5%
r	1276	5.3%
s	1103	4.6%
d	835	3.5%
Other values (65)	6733	27.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	24106	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	3379	14.0%
e	2185	9.1%
n	1867	7.7%
i	1799	7.5%
a	1693	7.0%
o	1680	7.0%
t	1556	6.5%
r	1276	5.3%
s	1103	4.6%
d	835	3.5%
Other values (65)	6733	27.9%

Hope_Optimism_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	668
True	331

Value	Count	Frequency (%)
False	668	66.9%
True	331	33.1%

Hope_Optimism_Evidence
Text

Distinct	333
Distinct (%)	33.3%
Missing	0
Missing (%)	0.0%
Memory size	94.6 KiB

Length

Max length	206
Median length	0
Mean length	37.784785
Min length	0

Characters and Unicode

Total characters	37747
Distinct characters	75
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	332 ?
Unique (%)	33.2%

Sample

1st row
2nd row
3rd row
4th row
5th row

Value	Count	Frequency (%)
a	455	7.8%
the	355	6.1%
and	297	5.1%
of	235	4.0%
for	212	3.6%
positive	187	3.2%
hope	170	2.9%
to	112	1.9%
offers	102	1.7%
sense	80	1.4%
Other values (1289)	3647	62.3%

Most occurring characters

Value	Count	Frequency (%)
	5520	14.6%
e	4075	10.8%
o	2784	7.4%
i	2498	6.6%
a	2208	5.8%
s	2182	5.8%
n	2099	5.6%
t	2068	5.5%
r	1741	4.6%
l	1153	3.1%
Other values (65)	11419	30.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	37747	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	5520	14.6%
e	4075	10.8%
o	2784	7.4%
i	2498	6.6%
a	2208	5.8%
s	2182	5.8%
n	2099	5.6%
t	2068	5.5%
r	1741	4.6%
l	1153	3.1%
Other values (65)	11419	30.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	37747	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	5520	14.6%
e	4075	10.8%
o	2784	7.4%
i	2498	6.6%
a	2208	5.8%
s	2182	5.8%
n	2099	5.6%
t	2068	5.5%
r	1741	4.6%
l	1153	3.1%
Other values (65)	11419	30.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	37747	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	5520	14.6%
e	4075	10.8%
o	2784	7.4%
i	2498	6.6%
a	2208	5.8%
s	2182	5.8%
n	2099	5.6%
t	2068	5.5%
r	1741	4.6%
l	1153	3.1%
Other values (65)	11419	30.3%

Personal_Identification_Present
Boolean

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

True	787
False	212

Value	Count	Frequency (%)
True	787	78.8%
False	212	21.2%

Personal_Identification_Evidence
Text

Distinct	789
Distinct (%)	79.0%
Missing	0
Missing (%)	0.0%
Memory size	157.7 KiB

Length

Max length	252
Median length	180
Mean length	101.41141
Min length	0

Characters and Unicode

Total characters	101310
Distinct characters	85
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	788 ?
Unique (%)	78.9%

Sample

1st row
2nd row	Directly targets 'Seniors' and 'Drivers Aged 70 and Above', creating immediate relevance for this demographic.
3rd row	Readers who are LGBTQ+, advocates for civil rights, or those with military connections may strongly identify with the cadets' situation and the implications of the decision.
4th row	The terms 'drivers' and 'millions of drivers' directly target and appeal to a very large and identifiable group of readers.
5th row	Appeals directly to regular McDonald's breakfast consumers who might be affected by the change.

Value	Count	Frequency (%)
the	1085	7.0%
to	624	4.0%
of	545	3.5%
and	543	3.5%
with	396	2.6%
or	389	2.5%
a	377	2.4%
directly	317	2.1%
in	240	1.6%
identify	237	1.5%
Other values (2233)	10710	69.3%

Most occurring characters

Value	Count	Frequency (%)
	14675	14.5%
e	10991	10.8%
i	6957	6.9%
t	6781	6.7%
a	6555	6.5%
n	6322	6.2%
o	5930	5.9%
r	5489	5.4%
s	5404	5.3%
l	4003	4.0%
Other values (75)	28203	27.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	101310	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	14675	14.5%
e	10991	10.8%
i	6957	6.9%
t	6781	6.7%
a	6555	6.5%
n	6322	6.2%
o	5930	5.9%
r	5489	5.4%
s	5404	5.3%
l	4003	4.0%
Other values (75)	28203	27.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	101310	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	14675	14.5%
e	10991	10.8%
i	6957	6.9%
t	6781	6.7%
a	6555	6.5%
n	6322	6.2%
o	5930	5.9%
r	5489	5.4%
s	5404	5.3%
l	4003	4.0%
Other values (75)	28203	27.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	101310	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	14675	14.5%
e	10991	10.8%
i	6957	6.9%
t	6781	6.7%
a	6555	6.5%
n	6322	6.2%
o	5930	5.9%
r	5489	5.4%
s	5404	5.3%
l	4003	4.0%
Other values (75)	28203	27.8%

Interactions

Correlations

	Authority_Present	Clarity_and_Conciseness_Value	Contains_Colon	Contains_Exclamation_Mark	Contains_Hyphen	Contains_Numbers	Contains_Question_Mark	Contains_Quotes	Curiosity_Present	Economic_Benefit_Present	Ends_With_Question_Mark	Exclusivity_Present	Exclusivity_Words	Fear_Concern_Present	Hope_Optimism_Present	Indignation_Controversy_Present	Length_General_Assessment	Length_Number_of_Characters	Main_Category	Main_Classification	National_Relevance_Present	Originality_and_Differentiation_Value	Personal_Identification_Present	Prohibition_Restriction_Present	Recognized_Brand_Present	Relevance_and_Timeliness_Value	Solution_Present	Starts_With_Number	Strategic_Keyword_Usage_Value	Surprise_Awe_Present	Temporal_Urgency_Present	Visibility
Authority_Present	1.000	0.028	0.006	0.000	0.000	0.000	0.000	0.000	0.082	0.000	0.000	0.000	0.022	0.131	0.033	0.072	0.050	0.246	0.266	0.340	0.047	0.046	0.047	0.117	0.025	0.075	0.000	0.045	0.054	0.000	0.000	1.000
Clarity_and_Conciseness_Value	0.028	1.000	0.000	0.000	0.000	0.000	0.000	0.070	0.000	0.042	0.000	0.000	0.000	0.031	0.018	0.064	0.582	0.765	0.154	0.070	0.107	0.110	0.059	0.016	0.068	0.000	0.000	0.042	0.111	0.060	0.056	1.000
Contains_Colon	0.006	0.000	1.000	0.000	0.107	0.000	0.018	0.237	0.134	0.019	0.000	0.086	0.175	0.044	0.000	0.000	0.000	0.143	0.187	0.455	0.000	0.147	0.000	0.000	0.000	0.015	0.000	0.063	0.085	0.058	0.036	1.000
Contains_Exclamation_Mark	0.000	0.000	0.000	1.000	0.000	0.020	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.059	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000
Contains_Hyphen	0.000	0.000	0.107	0.000	1.000	0.143	0.101	0.000	0.014	0.000	0.073	0.061	0.101	0.000	0.105	0.054	0.030	0.261	0.214	0.150	0.024	0.121	0.029	0.000	0.000	0.003	0.055	0.078	0.000	0.000	0.036	1.000
Contains_Numbers	0.000	0.000	0.000	0.020	0.143	1.000	0.116	0.000	0.076	0.206	0.083	0.064	0.062	0.046	0.011	0.000	0.000	0.107	0.147	0.296	0.000	0.045	0.000	0.000	0.000	0.000	0.034	0.300	0.000	0.128	0.084	1.000
Contains_Question_Mark	0.000	0.000	0.018	0.000	0.101	0.116	1.000	0.053	0.095	0.000	0.800	0.000	0.000	0.000	0.000	0.036	0.000	0.096	0.090	0.963	0.000	0.052	0.068	0.000	0.089	0.000	0.042	0.044	0.000	0.071	0.000	1.000
Contains_Quotes	0.000	0.070	0.237	0.000	0.000	0.000	0.053	1.000	0.102	0.000	0.028	0.054	0.187	0.000	0.087	0.146	0.088	0.316	0.270	0.569	0.122	0.238	0.000	0.000	0.069	0.127	0.138	0.040	0.095	0.177	0.045	1.000
Curiosity_Present	0.082	0.000	0.134	0.000	0.014	0.076	0.095	0.102	1.000	0.048	0.073	0.063	0.000	0.214	0.056	0.000	0.000	0.132	0.346	0.325	0.216	0.281	0.000	0.033	0.000	0.000	0.042	0.072	0.053	0.256	0.059	1.000
Economic_Benefit_Present	0.000	0.042	0.019	0.000	0.000	0.206	0.000	0.000	0.048	1.000	0.000	0.050	0.166	0.069	0.189	0.059	0.083	0.307	0.340	0.000	0.000	0.077	0.000	0.035	0.113	0.000	0.000	0.044	0.000	0.103	0.020	1.000
Ends_With_Question_Mark	0.000	0.000	0.000	0.000	0.073	0.083	0.800	0.028	0.073	0.000	1.000	0.000	0.000	0.000	0.000	0.019	0.000	0.000	0.086	0.791	0.000	0.068	0.037	0.000	0.059	0.000	0.000	0.025	0.000	0.054	0.000	1.000
Exclusivity_Present	0.000	0.000	0.086	0.000	0.061	0.064	0.000	0.054	0.063	0.050	0.000	1.000	0.986	0.070	0.036	0.000	0.051	0.117	0.137	0.151	0.000	0.127	0.066	0.000	0.000	0.031	0.000	0.007	0.159	0.150	0.000	1.000
Exclusivity_Words	0.022	0.000	0.175	0.000	0.101	0.062	0.000	0.187	0.000	0.166	0.000	0.986	1.000	0.000	0.057	0.000	0.195	0.000	0.124	0.163	0.000	0.119	0.159	0.066	0.000	0.207	0.000	0.000	0.471	0.148	0.052	1.000
Fear_Concern_Present	0.131	0.031	0.044	0.000	0.000	0.046	0.000	0.000	0.214	0.069	0.000	0.070	0.000	1.000	0.311	0.315	0.091	0.099	0.528	0.229	0.159	0.104	0.089	0.240	0.000	0.091	0.122	0.079	0.000	0.065	0.038	1.000
Hope_Optimism_Present	0.033	0.018	0.000	0.000	0.105	0.011	0.000	0.087	0.056	0.189	0.000	0.036	0.057	0.311	1.000	0.250	0.074	0.078	0.426	0.219	0.139	0.072	0.183	0.054	0.094	0.052	0.516	0.145	0.031	0.133	0.017	1.000
Indignation_Controversy_Present	0.072	0.064	0.000	0.000	0.054	0.000	0.036	0.146	0.000	0.059	0.019	0.000	0.000	0.315	0.250	1.000	0.141	0.331	0.366	0.248	0.116	0.175	0.063	0.102	0.075	0.000	0.173	0.045	0.000	0.166	0.000	1.000
Length_General_Assessment	0.050	0.582	0.000	0.000	0.030	0.000	0.000	0.088	0.000	0.083	0.000	0.051	0.195	0.091	0.074	0.141	1.000	0.659	0.192	0.217	0.072	0.148	0.044	0.000	0.051	0.000	0.044	0.056	0.123	0.089	0.056	1.000
Length_Number_of_Characters	0.246	0.765	0.143	0.000	0.261	0.107	0.096	0.316	0.132	0.307	0.000	0.117	0.000	0.099	0.078	0.331	0.659	1.000	0.000	0.000	0.123	0.368	0.155	0.195	0.147	0.189	0.000	0.200	0.696	0.243	0.194	0.032
Main_Category	0.266	0.154	0.187	0.059	0.214	0.147	0.090	0.270	0.346	0.340	0.086	0.137	0.124	0.528	0.426	0.366	0.192	0.000	1.000	0.174	0.502	0.240	0.395	0.361	0.375	0.152	0.472	0.232	0.111	0.364	0.141	1.000
Main_Classification	0.340	0.070	0.455	0.000	0.150	0.296	0.963	0.569	0.325	0.000	0.791	0.151	0.163	0.229	0.219	0.248	0.217	0.000	0.174	1.000	0.199	0.236	0.138	0.084	0.184	0.092	0.239	0.643	0.000	0.298	0.184	1.000
National_Relevance_Present	0.047	0.107	0.000	0.000	0.024	0.000	0.000	0.122	0.216	0.000	0.000	0.000	0.000	0.159	0.139	0.116	0.072	0.123	0.502	0.199	1.000	0.114	0.000	0.030	0.105	0.035	0.180	0.000	0.000	0.129	0.043	1.000
Originality_and_Differentiation_Value	0.046	0.110	0.147	0.000	0.121	0.045	0.052	0.238	0.281	0.077	0.068	0.127	0.119	0.104	0.072	0.175	0.148	0.368	0.240	0.236	0.114	1.000	0.224	0.000	0.066	0.032	0.096	0.024	0.098	0.547	0.000	1.000
Personal_Identification_Present	0.047	0.059	0.000	0.000	0.029	0.000	0.068	0.000	0.000	0.000	0.037	0.066	0.159	0.089	0.183	0.063	0.044	0.155	0.395	0.138	0.000	0.224	1.000	0.089	0.000	0.000	0.146	0.052	0.041	0.279	0.000	1.000
Prohibition_Restriction_Present	0.117	0.016	0.000	0.000	0.000	0.000	0.000	0.000	0.033	0.035	0.000	0.000	0.066	0.240	0.054	0.102	0.000	0.195	0.361	0.084	0.030	0.000	0.089	1.000	0.000	0.015	0.000	0.042	0.000	0.000	0.086	1.000
Recognized_Brand_Present	0.025	0.068	0.000	0.000	0.000	0.000	0.089	0.069	0.000	0.113	0.059	0.000	0.000	0.000	0.094	0.075	0.051	0.147	0.375	0.184	0.105	0.066	0.000	0.000	1.000	0.000	0.166	0.150	0.000	0.072	0.000	1.000
Relevance_and_Timeliness_Value	0.075	0.000	0.015	0.000	0.003	0.000	0.000	0.127	0.000	0.000	0.000	0.031	0.207	0.091	0.052	0.000	0.000	0.189	0.152	0.092	0.035	0.032	0.000	0.015	0.000	1.000	0.060	0.000	0.313	0.000	0.028	1.000
Solution_Present	0.000	0.000	0.000	0.000	0.055	0.034	0.042	0.138	0.042	0.000	0.000	0.000	0.000	0.122	0.516	0.173	0.044	0.000	0.472	0.239	0.180	0.096	0.146	0.000	0.166	0.060	1.000	0.059	0.051	0.159	0.009	1.000
Starts_With_Number	0.045	0.042	0.063	0.000	0.078	0.300	0.044	0.040	0.072	0.044	0.025	0.007	0.000	0.079	0.145	0.045	0.056	0.200	0.232	0.643	0.000	0.024	0.052	0.042	0.150	0.000	0.059	1.000	0.000	0.071	0.049	1.000
Strategic_Keyword_Usage_Value	0.054	0.111	0.085	0.000	0.000	0.000	0.000	0.095	0.053	0.000	0.000	0.159	0.471	0.000	0.031	0.000	0.123	0.696	0.111	0.000	0.000	0.098	0.041	0.000	0.000	0.313	0.051	0.000	1.000	0.022	0.000	1.000
Surprise_Awe_Present	0.000	0.060	0.058	0.000	0.000	0.128	0.071	0.177	0.256	0.103	0.054	0.150	0.148	0.065	0.133	0.166	0.089	0.243	0.364	0.298	0.129	0.547	0.279	0.000	0.072	0.000	0.159	0.071	0.022	1.000	0.061	1.000
Temporal_Urgency_Present	0.000	0.056	0.036	0.000	0.036	0.084	0.000	0.045	0.059	0.020	0.000	0.000	0.052	0.038	0.017	0.000	0.056	0.194	0.141	0.184	0.043	0.000	0.000	0.086	0.000	0.028	0.009	0.049	0.000	0.061	1.000	1.000
Visibility	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	0.032	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

	Title	Visibility	Cleaned_Headline	Main_Category	Subcategory_1	Subcategory_2	Clarity_and_Conciseness_Value	Clarity_and_Conciseness_Comment	Relevance_and_Timeliness_Value	Relevance_and_Timeliness_Comment	Strategic_Keyword_Usage_Value	Strategic_Keyword_Usage_Comment	Originality_and_Differentiation_Value	Originality_and_Differentiation_Comment	Contains_Numbers	Contains_Quotes	Contains_Question_Mark	Contains_Colon	Contains_Hyphen	Contains_Exclamation_Mark	Starts_With_Number	Ends_With_Question_Mark	Length_General_Assessment	Length_Number_of_Characters	Emphatic_Capitalization_Usage	Main_Classification	Comment_Type_Justification	Temporal_Urgency_Present	Temporal_Urgency_Words	Exclusivity_Present	Exclusivity_Words	Authority_Present	Authority_Words	Solution_Present	Solution_Words	Economic_Benefit_Present	Economic_Benefit_Words	Prohibition_Restriction_Present	Prohibition_Restriction_Words	National_Relevance_Present	National_Relevance_Words	Recognized_Brand_Present	Recognized_Brand_Words	Curiosity_Present	Curiosity_Evidence	Fear_Concern_Present	Fear_Concern_Evidence	Surprise_Awe_Present	Surprise_Awe_Evidence	Indignation_Controversy_Present	Indignation_Controversy_Evidence	Hope_Optimism_Present	Hope_Optimism_Evidence	Personal_Identification_Present	Personal_Identification_Evidence
0	Ford is forced to immediately shut down factories and halt car production as CEO admits 'day to day' struggle for brand	22572066	Ford is forced to immediately shut down factories and halt car production as CEO admits 'day to day' struggle for brand	Finance_and_Business	Companies & Entrepreneurship	N/A	High	The main message is very clear and easy to understand, detailing Ford's production halt and the CEO's admission of struggle.	High	The headline discusses a significant event for a major global brand, which is highly relevant and timely for business and general news audiences.	High	Key terms like 'Ford', 'factories', 'car production', 'CEO', and 'struggle' are used effectively, making the headline highly discoverable and appealing.	Medium	While the subject matter is impactful, the phrasing is a standard news report style, not particularly unique in its linguistic approach.	No	Yes	No	No	No	No	No	No	Adequate	105	No	Declarative Simple	The headline presents a series of factual statements about Ford's situation and the CEO's admission without posing a question, using urgency markers, or comparing elements.	Yes	["immediately"]	No	[]	Yes	["CEO admits"]	No	[]	No	[]	No	[]	No	[]	Yes	["Ford"]	No		Yes	The phrases 'forced to immediately shut down factories', 'halt car production', and 'struggle for brand' evoke concern about economic stability and the future of a major company.	No		No		No		No
1	New U.S. Driving License Rule for Seniors Begins July 2025 - Essential Changes for Drivers Aged 70 and Above	21331409	New U.S. Driving License Rule for Seniors Begins July 2025 - Essential Changes for Drivers Aged 70 and Above	News_and_Current_Events	Politics	Government	High	The main message is exceptionally clear, detailing who, what, and when without ambiguity.	High	Highly relevant to a specific, large demographic (seniors/drivers) and provides timely information about a future change.	High	Contains highly relevant keywords like 'U.S. Driving License Rule', 'Seniors', 'July 2025', 'Essential Changes', and 'Drivers Aged 70 and Above'.	Medium	While a standard news announcement format, the specific details make it distinct, yet it lacks a unique angle or creative phrasing.	Yes	No	No	No	Yes	No	No	No	Adequate	101	No	Declarative Simple	The headline directly states a new rule and its implications, serving as a straightforward announcement.	Yes	["Begins July 2025"]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["U.S."]	No	[]	Yes	The phrase 'Essential Changes' prompts readers to seek information on what those changes entail.	No		No		No		No		Yes	Directly targets 'Seniors' and 'Drivers Aged 70 and Above', creating immediate relevance for this demographic.
2	Cadets who met all Air Force Academy graduation standards denied commissions because they’re transgender	19344936	Cadets who met all Air Force Academy graduation standards denied commissions because they’re transgender	News_and_Current_Events	Politics	Government	High	The main message is very clear and direct, stating precisely what occurred and why.	High	The topic of transgender rights and military policy is highly current and relevant, resonating with ongoing social and political discussions.	High	Uses strong, specific keywords like 'Cadets', 'Air Force Academy', 'denied commissions', and 'transgender', which are highly relevant to the subject matter and discoverable.	Medium	The specific event described is notable, though the broader subject of transgender individuals in the military has been discussed before. It offers a distinct event within a known debate.	No	No	No	No	No	No	No	No	Adequate	106	No	Declarative Simple	The headline makes a direct statement about an event, presenting it as a fact without using a question, direct quote, or emphasizing urgency.	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["denied"]	No	[]	No	[]	No		No		No		Yes	The phrase 'denied commissions because they’re transgender' directly implies a potential act of discrimination, which is highly likely to provoke indignation and controversy among various audiences.	No		Yes	Readers who are LGBTQ+, advocates for civil rights, or those with military connections may strongly identify with the cadets' situation and the implications of the decision.
3	The DMV confirms it - The United States is ending the benefit that allowed drivers to drive with an expired license without immediate renewal - millions of drivers will have to renew urgently	18797641	The DMV confirms it - The United States is ending the benefit that allowed drivers to drive with an expired license without immediate renewal - millions of drivers will have to renew urgently	News_and_Current_Events	Politics	Government	High	The main message is very clear and direct, stating the change, its source, and its impact.	High	Highly relevant as it affects a large demographic ('millions of drivers') and requires urgent action, indicating timeliness.	High	Uses strong keywords like 'DMV', 'United States', 'expired license', 'drivers', and 'renew urgently', which are highly searchable and relevant.	Medium	While the specific policy change is unique, the headline structure (authority confirms X - consequence) is common. Its strength lies in the immediate, widespread impact.	Yes	No	No	No	Yes	No	No	No	Adequate	173	No	Urgency	The headline clearly states a new policy confirmed by an authority and strongly emphasizes the immediate, widespread need for action, particularly with the phrase 'renew urgently' affecting 'millions of drivers'.	Yes	["immediate","urgently"]	No	[]	Yes	["DMV","confirms"]	No	[]	No	[]	Yes	["ending the benefit","without immediate renewal"]	Yes	["United States"]	Yes	["DMV"]	No		Yes	The phrase 'millions of drivers will have to renew urgently' directly implies potential negative consequences or significant inconvenience if the reader fails to act, evoking concern.	No		No		No		Yes	The terms 'drivers' and 'millions of drivers' directly target and appeal to a very large and identifiable group of readers.
4	McDonald's Removing 1 Breakfast Menu Item for Good on July 2	16353543	McDonald's Removing 1 Breakfast Menu Item for Good on July 2	Gastronomy	Restaurants & Chefs	N/A	High	The message is clear and to the point, identifying the brand, action, and date.	High	Highly relevant for McDonald's customers and tied to a specific future date, July 2.	High	Uses strong keywords like 'McDonald's', 'Breakfast Menu', and 'Removing', appealing to target audience interests.	Medium	While common for fast-food news, the specificity of '1 Breakfast Menu Item' and 'for Good' provides some differentiation.	Yes	No	No	No	No	No	No	No	Adequate	57	No	Declarative Simple	The headline directly states a fact without posing a question, using a quote, or indicating urgency beyond the date.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["McDonald's"]	Yes	The headline creates an information gap by not revealing which specific breakfast item is being removed.	Yes	The phrase 'Removing... for Good' could evoke concern among customers about a favorite item.	No		No		No		Yes	Appeals directly to regular McDonald's breakfast consumers who might be affected by the change.
5	The DMV confirms it—people over 70 will have to meet new requirements to keep their driver's license in the United States	15318643	The DMV confirms it—people over 70 will have to meet new requirements to keep their driver's license in the United States	News_and_Current_Events	Politics	Government	High	The main message about new DMV requirements for older drivers is very clear and easy to understand.	High	Driving regulations, especially those affecting a specific age group, are highly relevant to a large demographic and are a recurring topic of public interest.	High	Keywords like 'DMV', '70', 'driver's license', and 'United States' are highly relevant and likely to be searched for or noticed by the target audience.	Medium	The headline is specific about the authority ('DMV confirms it') and the demographic, which gives it some differentiation from generic news, but the structure is standard.	Yes	No	No	No	Yes	No	No	No	Adequate	106	No	Declarative Simple	The headline directly states a fact confirmed by an authority, informing the reader of a new regulation without posing a question or implying a mystery.	No	[]	No	[]	Yes	["confirms","DMV"]	No	[]	No	[]	Yes	["will have to meet new requirements","keep their driver's license"]	Yes	["United States"]	Yes	["DMV"]	Yes	The mention of 'new requirements' without specifying them creates an information gap, prompting readers to click to learn what these changes entail.	Yes	The phrase 'will have to meet new requirements to keep their driver's license' can evoke concern or anxiety for older drivers about their ability to retain their driving privileges and independence.	No		No		No		Yes	The headline directly addresses and impacts 'people over 70', creating strong personal identification for individuals in that age group and their families.
6	Goodbye to retirement at 65: Social Security sets a new retirement age from 2026	14627061	Goodbye to retirement at 65: Social Security sets a new retirement age from 2026	Finance_and_Business	Personal_Finance	Retirement	High	The main message is immediately clear: the retirement age is changing.	High	The topic of retirement age and Social Security is highly relevant to a broad audience and includes a specific future date ('from 2026') indicating timeliness.	High	Key terms like 'retirement,' 'Social Security,' and 'retirement age' are highly strategic and likely to be searched by interested individuals.	Medium	While retirement changes are common news, the opening phrase 'Goodbye to retirement at 65' adds an impactful and somewhat unique framing.	Yes	No	No	Yes	No	No	No	No	Adequate	70	No	Declarative Simple	The headline presents a direct statement of fact about a change in the retirement age.	Yes	["from 2026"]	No	[]	Yes	["Social Security"]	No	[]	No	[]	No	[]	No	[]	Yes	["Social Security"]	Yes	The phrase 'Goodbye to retirement at 65' immediately piques curiosity about what the new age will be and why the change is happening.	Yes	The headline could evoke concern among readers about their financial future and the implications of a later retirement.	Yes	The news of a fundamental shift in retirement age, a long-established concept, can be surprising.	Yes	Changes to social programs like retirement age frequently generate public debate and potential indignation.	No		Yes	The topic of retirement and Social Security directly affects the financial planning and future of many individuals, leading to strong personal identification.
7	Elon Musk gave Apple 72 hours to accept his $5 billion offer. Tim Cook said no, so Elon followed through with his threat.	13507301	Elon Musk gave Apple 72 hours to accept his $5 billion offer. Tim Cook said no, so Elon followed through with his threat.	Finance_and_Business	Companies & Entrepreneurship	N/A	High	The main message is very clear, detailing the involved parties, the offer, the rejection, and the subsequent action, without ambiguity.	High	Features highly relevant and frequently discussed figures (Elon Musk, Tim Cook) and companies (Apple), ensuring strong general interest.	High	Includes prominent keywords such as 'Elon Musk', 'Apple', 'Tim Cook', and '$5 billion', which are highly searchable and appealing to a broad audience.	High	The narrative of a public challenge, rejection, and explicit follow-through on a 'threat' provides a unique and dramatic angle that stands out.	Yes	No	No	No	No	No	No	No	Adequate	104	No	Declarative Simple	The headline presents a straightforward statement of facts without posing a question, quoting directly, or explicitly indicating urgency.	Yes	["72 hours"]	No	[]	No	[]	No	[]	Yes	["$5 billion"]	No	[]	No	[]	Yes	["Elon Musk","Apple","Tim Cook"]	Yes	The phrase 'followed through with his threat' creates an information gap, compelling the reader to wonder what the threat was and its consequences.	No		Yes	The audacious $5 billion offer with a short ultimatum and the dramatic follow-through on a 'threat' can evoke surprise.	Yes	The nature of the 'threat' and its execution can spark debate or strong opinions about the involved parties' actions.	No		No
8	90s Country Icon’s Teeth Fall Out Mid-Performance During Washington Concert: “The Show Must Go On”	13339952	90s Country Icon’s Teeth Fall Out Mid-Performance During Washington Concert: “The Show Must Go On”	Entertainment_and_Culture	Celebrities_and_Influencers	N/A	High	The main message is straightforward and easy to understand, describing a highly unusual and specific event.	High	The headline describes an unusual and attention-grabbing incident involving a celebrity, which is highly relevant to current interests in entertainment news.	High	Keywords like "90s Country Icon," "Teeth Fall Out," and "Mid-Performance" are highly specific and engaging, likely to capture audience attention.	High	The event described is extremely unusual and therefore the headline is highly original and stands out from typical news.	Yes	Yes	No	Yes	No	No	Yes	No	Adequate	101	Yes, "The Show Must Go On", justified use as it is a direct quote.	Direct Quote	The headline prominently features a direct quote from the event, which is essential to its content and impact.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Washington"]	No	[]	Yes	The phrase "Teeth Fall Out Mid-Performance" creates a strong information gap and immediately makes the reader curious about the circumstances.	No		Yes	The highly unexpected and bizarre nature of "Teeth Fall Out Mid-Performance" elicits surprise and possibly a sense of awe at the unusual incident.	No		No		No
9	Americans who own refrigerators from 3 brands to get $300 from settlement	13255807	Americans who own refrigerators from 3 brands to get $300 from settlement	Finance_and_Business	Personal_Finance	N/A	High	The main message is very clear: certain Americans will receive money due to a settlement.	High	Directly impacts a large segment of the population (Americans who own specific appliances) and offers a tangible benefit (money from a settlement).	High	Includes highly relevant keywords like 'Americans', 'refrigerators', 'brands', '$300', and 'settlement', which are likely search terms for interested individuals.	Medium	While the specific settlement details are unique, the headline structure of 'who gets money from X' is a common news format. The unnamed brands reduce its immediate differentiation.	Yes	No	No	No	No	No	No	No	Adequate	70	No	Declarative Simple	The headline presents a direct and straightforward statement of fact without asking a question, making a comparison, or implying urgency.	No	[]	No	[]	No	[]	No	[]	Yes	["$300","settlement"]	No	[]	Yes	["Americans"]	No	[]	Yes	The mention of '3 brands' creates a curiosity gap, prompting readers to click to find out which brands are involved.	No		No		No		Yes	The prospect of receiving $300 from a settlement evokes a sense of hope and financial optimism for those who qualify.	Yes	Americans who own refrigerators' directly targets a broad demographic, encouraging self-identification and relevance.

	Title	Visibility	Cleaned_Headline	Main_Category	Subcategory_1	Subcategory_2	Clarity_and_Conciseness_Value	Clarity_and_Conciseness_Comment	Relevance_and_Timeliness_Value	Relevance_and_Timeliness_Comment	Strategic_Keyword_Usage_Value	Strategic_Keyword_Usage_Comment	Originality_and_Differentiation_Value	Originality_and_Differentiation_Comment	Contains_Numbers	Contains_Quotes	Contains_Question_Mark	Contains_Colon	Contains_Hyphen	Contains_Exclamation_Mark	Starts_With_Number	Ends_With_Question_Mark	Length_General_Assessment	Length_Number_of_Characters	Emphatic_Capitalization_Usage	Main_Classification	Comment_Type_Justification	Temporal_Urgency_Present	Temporal_Urgency_Words	Exclusivity_Present	Exclusivity_Words	Authority_Present	Authority_Words	Solution_Present	Solution_Words	Economic_Benefit_Present	Economic_Benefit_Words	Prohibition_Restriction_Present	Prohibition_Restriction_Words	National_Relevance_Present	National_Relevance_Words	Recognized_Brand_Present	Recognized_Brand_Words	Curiosity_Present	Curiosity_Evidence	Fear_Concern_Present	Fear_Concern_Evidence	Surprise_Awe_Present	Surprise_Awe_Evidence	Indignation_Controversy_Present	Indignation_Controversy_Evidence	Hope_Optimism_Present	Hope_Optimism_Evidence	Personal_Identification_Present	Personal_Identification_Evidence
989	New tax hikes on a variety of items coming to Illinois next month. Here's what prices are going up and when	590578	New tax hikes on a variety of items coming to Illinois next month. Here's what prices are going up and when	Finance_and_Business	Personal Finance	N/A	High	The headline clearly states the subject (tax hikes), location (Illinois), and implication (prices going up), and when (next month).	High	The topic of tax hikes and rising prices is highly relevant to personal finance and timely due to the 'next month' mention.	High	Uses strong keywords like 'tax hikes', 'Illinois', and 'prices going up' which are highly relevant and searchable.	Medium	While tax hike news is common, the second sentence directly addressing 'what prices' and 'when' adds a valuable and somewhat unique angle, though the core topic is not novel.	No	No	No	Yes	No	No	No	No	Adequate	101	No	Mystery/Revelation	The headline, particularly the second part 'Here's what prices are going up and when', promises to reveal specific information, creating an information gap that readers will want to fill.	Yes	["next month"]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Illinois"]	No	[]	Yes	Here's what prices are going up and when	Yes	New tax hikes, prices are going up	No		Yes	New tax hikes	No		Yes	Illinois, prices are going up
990	Illinois residents' information accessed in data breach, Healthcare and Family Services says	589230	Illinois residents' information accessed in data breach, Healthcare and Family Services says	News_and_Current_Events	Crime & Judicial	N/A	High	The main message is clear and easy to understand, directly stating the event and its source.	High	Data breaches are a highly relevant and timely topic, especially for the affected demographic.	High	The headline effectively uses relevant keywords such as "Illinois residents", "information accessed", and "data breach".	Medium	While data breaches are common, the specific mention of "Illinois residents" and the government agency provides some differentiation.	No	No	No	No	No	No	No	No	Adequate	84	No	Attribution ('according to', 'reveals')	The headline explicitly states the source of the information, "Healthcare and Family Services says", making it an attribution type.	No	[]	No	[]	Yes	["says"]	No	[]	No	[]	No	[]	Yes	["Illinois"]	Yes	["Healthcare and Family Services"]	No		Yes	The phrase "data breach" and "information accessed" immediately triggers concern regarding personal security and privacy.	No		No		No		Yes	The mention of "Illinois residents" directly targets and makes the headline relevant to a specific audience.
991	A Buc-ee’s competitor is marking its territory across Texas	588887	A Buc-ee’s competitor is marking its territory across Texas	Finance_and_Business	Companies & Entrepreneurship	Competition	High	The headline is very clear and easy to understand.	High	Highly relevant to Texans and those interested in travel/business news due to the popularity of Buc-ee's.	High	Uses strong keywords like "Buc-ee's", "competitor", and "Texas" which are highly appealing to the target audience.	High	The phrase "marking its territory" adds a unique and evocative angle, making it stand out.	No	No	No	No	Yes	No	No	No	Adequate	55	No	Declarative Simple	The headline makes a straightforward statement of fact without asking a question, quoting someone, or indicating urgency.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Texas"]	Yes	["Buc-ee’s"]	Yes	The mention of a "Buc-ee’s competitor" and "marking its territory" creates an information gap, making the reader curious about who the competitor is and what they are doing.	No		No		No		No		Yes	The headline directly appeals to individuals who are familiar with or reside in Texas and are aware of Buc-ee's.
992	Sam's Club sends a last-minute message to its members: It's here already	587557	Sam's Club sends a last-minute message to its members: It's here already	Finance_and_Business	Companies & Entrepreneurship	N/A	High	The main message is clear about the sender and recipient, and implies an important arrival.	High	The 'last-minute' and 'already' phrases create immediate relevance and urgency for Sam's Club members.	Medium	Uses "Sam's Club" and "members" which are relevant, but the ambiguous "It's here already" might not optimize for specific searches.	Medium	The specific phrasing with the intriguing "It's here already" provides a unique angle compared to a purely informative headline.	No	Yes	No	Yes	Yes	No	No	No	Adequate	70	No	Mystery/Revelation	The headline hints at the arrival of something significant ("It's here already") but doesn't reveal what it is, thereby building anticipation and curiosity.	Yes	["last-minute","already"]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Sam's Club"]	Yes	The phrase 'It's here already' creates an information gap, making the reader wonder what 'it' is.	No		No		No		No		Yes	The phrase 'to its members' directly targets a specific audience, making the message feel personal and relevant to them.
993	Jennifer Aniston's home features the most glamorous garden lounge we've ever seen – it is five-star perfection	586529	Jennifer Aniston's home features the most glamorous garden lounge we've ever seen – it is five-star perfection	Home_and_Lifestyle	Decoration_and_Interior_Design	N/A	High	The message is very clear and easy to understand, directly stating the subject and its perceived quality.	High	Celebrity homes and interior design are consistently high-interest evergreen topics.	High	Uses strong keywords like 'Jennifer Aniston', 'home', 'garden lounge', and descriptive terms like 'glamorous' and 'five-star perfection' appealing to the target audience.	Medium	While celebrity home features are common, the strong superlative claim of "most glamorous...we've ever seen" provides a level of differentiation.	Yes	No	No	No	No	No	No	No	Adequate	80	No	Superlative	The headline explicitly uses superlative language such as "most glamorous" and "five-star perfection" to describe the subject.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["Jennifer Aniston"]	Yes	The phrase "the most glamorous garden lounge we've ever seen – it is five-star perfection" creates an information gap, making readers curious to see what makes it so exceptional.	No		Yes	The strong superlative "most glamorous" and "five-star perfection" is intended to evoke a sense of awe and wonder at the described feature.	No		No		Yes	Readers can easily imagine and aspire to have such a glamorous feature in their own homes, leading to personal identification with the desirable element.
994	18 High-Protein No-Cook Recipes for Dinner Tonight	585428	18 High-Protein No-Cook Recipes for Dinner Tonight	Gastronomy	Recipes	Main Courses	High	The main message is very clear: 18 high-protein, no-cook recipes for dinner tonight. No ambiguity.	High	Highly relevant to current interests in healthy eating and convenience, with a clear timely hook ("Tonight").	High	Uses strong keywords like "High-Protein", "No-Cook", "Recipes", and "Dinner Tonight" that align with user searches and interests.	Medium	While recipe headlines are common, the specific combination of "High-Protein" and "No-Cook" offers a somewhat unique and appealing angle.	Yes	No	No	No	Yes	No	Yes	No	Adequate	53	No	List/Numbered	The headline explicitly starts with a number (18), indicating a list of items.	Yes	["Tonight"]	No	[]	No	[]	Yes	["Recipes","No-Cook"]	No	[]	Yes	["No-Cook"]	No	[]	No	[]	Yes	The specific number "18" and the unique combination of "High-Protein" and "No-Cook" create an information gap that sparks curiosity about the recipes themselves.	No		No		No		Yes	Offers a convenient, healthy, and easy solution for dinner, evoking a sense of relief and positivity.	Yes	Directly addresses a common need ("for Dinner Tonight") and targets individuals seeking healthy ("High-Protein") and easy ("No-Cook") meal solutions, making it highly relatable.
995	Map Shows the 50 Best School Districts Across US	585417	Map Shows the 50 Best School Districts Across US	Education_and_Guides	Academic Advice	N/A	High	The main message is very clear and easy to understand.	High	Education quality and school rankings are consistently relevant to a broad audience.	High	Uses highly relevant keywords like "Map", "50 Best", "School Districts", and "US".	Medium	While listicles are common, the "Map Shows" aspect adds a slight visual and informative differentiator.	Yes	No	No	No	No	No	No	No	Adequate	46	No	List/Numbered ('50 Best')	The headline explicitly mentions "the 50 Best", classifying it as a numbered list and superlative.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["US"]	No	[]	Yes	The headline creates an information gap by promising to reveal the "50 Best School Districts" that a map shows.	No		No		No		Yes	The phrase "Best School Districts" appeals to the hope of finding quality education and a positive future.	Yes	The topic of school districts in the "US" directly appeals to parents, students, and educators residing in the country.
996	GPS-based speed limiter will be mandatory ― One state approves it and announces the date	585267	GPS-based speed limiter will be mandatory ― One state approves it and announces the date	News_and_Current_Events	Politics	Government	High	The headline clearly states the core news: a specific technology will be mandatory and a government has approved it.	High	The topic of speed limiters and traffic regulations is of great interest to the general public, especially drivers.	High	Uses specific and relevant keywords like 'GPS-based speed limiter' and 'mandatory', which attract a targeted audience.	Medium	While the 'X will be mandatory' format is common, the specific subject (GPS speed limiter) provides significant novelty.	No	No	No	No	Yes	No	No	No	Adequate	89	No	Declarative Simple	The headline makes a direct statement about a new regulation being approved, presenting it as a fact.	No	[]	No	[]	Yes	["mandatory","approves"]	No	[]	No	[]	Yes	["limiter","mandatory"]	No	[]	No	[]	Yes	The phrases 'One state' and 'announces the date' create a knowledge gap, motivating the user to click to find out the specific details.	Yes	The implementation of a 'mandatory' 'speed limiter' can cause concern among drivers about new traffic restrictions and potential penalties.	No		Yes	The mandatory nature of a speed limiter is a controversial topic that can provoke indignation and debate among citizens.	No		Yes	The headline directly addresses drivers and vehicle owners, a group that personally identifies with the regulation.
997	McDonald's Is Bringing Back a Sandwich We Never Thought We'd See Again	583765	McDonald's Is Bringing Back a Sandwich We Never Thought We'd See Again	Gastronomy	Restaurants & Chefs	N/A	High	The main message is immediately clear and easy to understand.	High	Food news, especially about popular fast-food chains and nostalgic items, generally has high relevance and evergreen interest.	High	Uses strong, relevant keywords like 'McDonald's' and 'Sandwich', which are highly searchable and appealing to the target audience.	Medium	While the theme of a returning menu item is common, the phrase "We Never Thought We'd See Again" adds a unique angle and creates intrigue.	No	No	No	No	No	No	No	No	Adequate	66	No	Mystery/Revelation ('secret', 'truth')	The headline creates a strong sense of mystery and anticipation by implying the return of a popular item that was believed to be gone forever, compelling the reader to discover what it is.	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	No	[]	Yes	["McDonald's"]	Yes	The phrase "We Never Thought We'd See Again" creates an information gap, making readers curious about which sandwich is returning.	No		Yes	The unexpected return implied by "We Never Thought We'd See Again" evokes surprise and a sense of delight for fans of the item.	No		Yes	For fans of the particular sandwich, its return brings a sense of hope and optimism about being able to enjoy it again.	Yes	The use of "We" directly includes the reader, fostering a sense of shared nostalgia and anticipation for the returning item.
998	This City Was Just Named the No. 1 Place to Live in the U.S. for Affordability and Cost of Living	582886	This City Was Just Named the No. 1 Place to Live in the U.S. for Affordability and Cost of Living	Finance_and_Business	Personal_Finance	N/A	High	The message is very clear and easy to understand, directly stating the city was named No. 1 for living due to affordability.	High	Topics like cost of living and affordability are evergreen and highly relevant to a broad audience, especially in current economic climates.	High	Keywords like "City," "No. 1 Place to Live," "U.S.," "Affordability," and "Cost of Living" are highly relevant and appealing to the target audience.	Medium	While the "No. 1 place to live" trope is common, the addition of "Affordability and Cost of Living" provides a specific and relevant angle.	Yes	No	No	No	No	No	No	No	Adequate	84	No	Superlative	The headline uses "No. 1" to highlight a top ranking, which is a superlative statement.	No	[]	No	[]	No	[]	No	[]	Yes	["Affordability","Cost of Living"]	No	[]	Yes	["U.S."]	No	[]	Yes	The headline intentionally withholds the name of 'This City,' prompting the reader to click to discover its identity.	No		No		No		Yes	The headline suggests finding an ideal living situation, especially concerning financial aspects ('Affordability and Cost of Living').	Yes	The topic of 'place to live' and 'cost of living' directly relates to personal well-being and financial concerns that many readers share.

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