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In the hit movie Letters to Juliet (2010), Sophie meets a guy she likes and has an exchange with him while on the balcony. As we learn, Sophie misunderstood several key facts about the guy she liked and they reunite their romance. Sophie's numerous inaccurate but consequential assumptions demonstrate a below-average example of the Inference attribute.
Feels Score: 4 in
Carrie's walk and outfit through NYC gets ruined by water

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Carrie Bradshaw is walking through New York City and plotting her next move right before a car passing by splashes her with water.

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In Katy Perry's hit single "Roar" (2013), the musical artist inspired millions around the world to embrace their own inner spirit animal. The powerful lyrics feature nature and wild animals as a core theme. However, listeners are left with many questions regarding many ambiguous lines. For example, the phrase "You held me down, but I got up (hey)" begs several questions: who is Perry referring to and what incident is she referencing, if real at all? It could be a figure of speech or a literal reference to the tragedy of domestic abuse. Lines like these and "I let you push me past the breaking point / I stood for nothing, so I fell for everything" require context not provided by Katy Perry, and this lack of detail demonstrates a well below-average example of the Specificity attribute.
Feels Score: 3 in

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Popular children's television show host and producer testified before congress in 1969 in order to secure funding for public broadcasting. After only six minutes of speaking, Mister Rogers secured twenty million dollars in his party's favor. Everyone present understood the nature and importance of Roger's work alongside its impact on both young children and the future of America.
Feels Score: 8 in

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In the hit movie Sunshine (2007), Searle is a space mission psychiatrist who is obsessed with the sun. He is in the observation room and asks the ships' onboard AI to turn up the brightness. The ship's AI indicates that he can only view a portion of the sun's brightness for 30 seconds or else he would damage his eyes. After agreeing, Searle gets enveloped by bright sunlight. Searle's use of words related to color, coloration, and visual sense perception demonstrate the Sensation attribute.
Feels Score: 6 in
Feels – Laugh. Learn. Language™

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Feels – Psycholinguistics made simple. Our mission is to promote objective analysis of real 🗣️human language via fun, short videos and the 🪄magic of psycholinguistics. We do this by organizing, analyzing, and making freely available a growing collection of Feels, or highly structured short-form videos that explain the contents of a given conversation between two or more people. Plus GIFs.

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.