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In Superman (2025), Lex Luthor is confronted by Superman (Clark Kent) for stealing his dog. Superman storms in Lex's office in the city and flips his desk, demanding to know the location of his dog, Krypto. Lex lies to Superman while holding a stern glaze and sipping his coffee. Lex then makes a comment under his breath about how the dog wears a cape, making it plain to all that Lex in fact stole Superman's dog. Lex's ability to deceive Superman while giving himself away demonstrates an above-average example of the Apperception attribute.
Feels Score: 6 in

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In Taylor Swift's hit 2014 album called "1989," the single track called "Shake it Off" gained worldwide attention for its catchy beat and dismissal of negativity surrounding Swift's public image. Indeed, the lyrics repeat phrases like "the haters gonna hate, hate, hate, hate, hate." Compared to Swift's other songs, "Shake it Off" is unique because there is limited mention of personal romance, drama, and feelings. Rather, the song uses words and phrases related to Swift's intended actions, not her emotional state. Taylor Swift's slight use of language related to positive and negative affect demonstrate an above average example of the Emotion attribute.
Feels Score: 6 in

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Jim questions William about Delos investing in the Westworld theme park.
Feels Score: 3 in

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In the hit movie Arrival, Dr. Louise Banks, played by Amy Adams, explains to her military counterpart why she must teach the alphabet to aliens that recently arrived on Earth for an unknown purpose.
Feels Score: 9 in
Bill Gates really can dance and even jump over chairs!

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Bill Gates shows us how in the 1980s he had a strong sense of humor alongside the ability to jump over a chair.
LINGA – Our business is language itself™

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LINGA is a psycholinguistics technology company that provides authorship identity verification as a service via our proprietary Linguistic Fingerprint™ technology. Through the LINGA web application, guests complete writing prompts in order to build their Linguistic Fingerprint™. Once built, guests can discover their true selves as expressed in the form-factor of writing. Guests can also scan written documents in order to generate a unique Authorship Verification Certificate, which is certified by LINGA and available as a downloadable PDF file. This certificate indicates whether or not the scanned document matches our guest's Linguistic Fingerprint™, and is backed by our $1,000,000 Authorship Integrity Defense Guarantee (SM · Terms apply). Individual guests can use LINGA to verify and defend authorship integrity for important written works like books, articles, papers, speeches, and more.

Ultra Low

0–5% percentile
An ultra low attribute score is exceptionally rare because it represents 5% of the entire population. In a room with 100 other people, a person with an ultra low attribute score would be lower than 95 of them and higher than none of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Very Low

5–10% percentile
A very low attribute score is rare because it represents 5% of the entire population. In a room with 100 other people, a person with a very low attribute score would be higher than five of them and lower than 90 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Low

10–20% percentile
A low attribute score is somewhat uncommon and represents 10% of the entire population. In a room with 100 other people, a person with a low attribute score would be higher than ten of them and lower than 80 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Slightly Low

20–40% percentile
A slightly low attribute score is common and represents 20% of the entire population. In a room with 100 other people, a person with a slightly low attribute score would be higher than 20 of them and lower than 60 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Average

40–60% percentile
An average attribute score is typical and represents 20% of the entire population. In a room with 100 other people, a person with an average attribute score would be higher than 40 of them and lower than 40 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Slightly High

60–80% percentile
A slightly high attribute score is common and represents 20% of the entire population. In a room with 100 other people, a person with a slightly high attribute score would be higher than 60 of them and lower than 20 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

High

80–90% percentile
A high attribute score is somewhat uncommon and represents 10% of the entire population. In a room with 100 other people, a person with a high attribute score would be higher than 80 of them and lower than 10 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Very High

90–95% percentile
A very high attribute score is rare because it represents 5% of the entire population. In a room with 100 other people, a person with a very high attribute score would be higher than 90 of them and lower than five of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.

Ultra High

95–100% percentile
An ultra high attribute score is exceptionally rare because it represents 5% of the entire population. In a room with 100 other people, a person with an ultra high attribute score would be higher than 95 of them and lower than none of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.