Feels – Laugh. Learn. Language.

Info

About · Method · Help

Legal

Terms · Privacy · DMCA

© 2025 Feels Co.

The Architect likes to use BIG words like "apropos" and "ergo"

Summary & key points

In the hit sequel to the Matrix (1999), The Matrix Reloaded (2003) features the creator of it all. The Architect meets Neo and explains his machine-like understanding of what happens next in not-so-simple language.

Feels in

Charlotte York reunites with Harry in a touching moment with a happy ending

Summary & key points

In season 6, episode 6 ("Hop, Skip and a Week") of Sex and the City (2003), Charlotte finds Harry at a singles event at the synagogue and he proposes to her. Before he did, Charlotte let Harry know how much she missed him and adored him. Her strong affection and teary-eyed condition demonstrates the Emotion attribute.

Feels in

Explicit Basketball coach Bob Knight loses it during halftime pep talk

Summary & key points

Bob Knight drops 17 f**** bombs in under 90 seconds.

Feels in

Wednesday Addams doesn't have time to interpret "emotional morse code"

Summary & key points

In season 1, episode 4 of the hit Netflix show called Wednesday (2022), teenager Wednesday Addams is discussing plans for going to a school dance with a certain someone. In typical Wednesday fashion, she redirected the conversation from her feelings to her priorities. This was highlighted when Wednesday said that it's not her fault for being unable to interpret "emotional morse code." Her lack of interest in discussing feelings and emotions and word choices reflect the Emotion attribute.

Feels in

Justin Bieber's lyrics in the 'Despacito' remix are not what you think

Summary & key points

In 2017, the popular Spanish song "Despacito" by Luis Fonsi and Daddy Yankee was remixed with the inclusion of Justin Bieber. The new "Despacito - Remix" version includes Bieber singing in both English and Spanish. During the English portion, the lyrics recount longing and passion for a romantic partner. Lyrics like "My sunrise on the darkest day / Got me feelin' some kind of way" and "The way you nibble on my ear, the only words I wanna hear" reference visual, physical, and auditory sensory perception, and demonstrate a typical example of the Sensation attribute.

Feels in

The Mask escapes police via dancing to "Cuban Pete"

Summary & key points

Stanley Ipkiss transforms for the first time.

Feels in

1
2
3
4
5
6
7
8
9
10

- Home ·
- Explore ·
- Help ·
- Terms ·
- Privacy
© Linguistic Innovations Natural Grammar Applications Co. dba Feels Co. All rights reserved. 2810 N Church St, #790324, Wilmington, DE 19802 US

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.