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MyLFP™ by LINGA – Introducing the Linguistic Fingerprint™

Summary & key points

It’s time to go beyond legacy methods of detecting plagiarism or AI-generated content. The Linguistic Fingerprint™ by LINGA is a revolutionary language analysis technology that sits at the intersection of linguistics, psychology, and computer science. It’s an entirely new way of identifying a person in the form-factors of speech and writing. Linguistic self-discovery awaits.

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Bill Gates answers lawyer's questions with "I'm not sure what you mean"

Summary & key points

In 1998, the Department of Justice sued Microsoft for antitrust violations. Bill Gates, the founder and leader of the company, had to testify. In widely circulated videos, Gates is shown evading some questions on the grounds that he does not understand. The lawyer tried to corner Gates on many occasions, without success.

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Lois Lane wants to talk about her relationship with Superman

Summary & key points

In Superman (2025), Lois Lane wants to talk about her relationship status with Superman (Clark Kent) and Mister Terrific doesn't want to.

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The Man in Black from Westworld

Summary & key points

The Man in Black from Westworld disrupts a therapy session and shares his views of the world and people.

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Carrie Bradshaw's fiancé Mr. Big humiliates the New York socialite on their wedding day by leaving

Summary & key points

In the movie Sex and the City (2008), Carrie is about to get married to John James Preston, or Mr. Big, and he gets cold feet while watching Carrie in his limousine. Carrie and Mr. Big speak on the phone and he tells her that he can't get married to her. Then, Mr. Big changes his mind as he is being driven and spots Carrie in the car on the other side of the road. They both pull over, get out, and confront one another. Although Mr. Big apologizes and seems as though he wants to get married – the events were too much for Carrie to bear – and she lashes out with her words and flowers at Mr. Big. She explains how she knew that he was going to do that, and how he humiliated her, all before Carrie's friends take her back into a vehicle and exit. Carrie's tears, physical aggression, and feelings of humiliation highlight an extreme instance of the Emotion attribute.

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Blondie's potential mate in Heart of Glass soon turned out to be a "pain in the a**"

Summary & key points

In rock band Blondie's 1978 hit single called Heart of Glass, the lyrics tell us about the potential disappointment of romance. The entire song features a single example of colorful language: "... soon turned out to be a pain in the a**." This limited, tame use of colorful language exemplifies the Formality attribute.

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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.