feeldb

Trading Places

1983 · 116 min · Director: John Landis ★ IMDb 7.5 · 185,164 ratings

Show plot summary (may contain spoilers)

A snobbish investor and a wily street con-artist find their positions reversed as part of a bet by two callous millionaires.

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Emotional fingerprint

Trading Places (1983) — Movie. Top emotional signals: Humor 35%, Excitement 25%, Satisfaction 20%. Source: AI estimate. Shares describe emotional signal, not percentages of people. Your experience may differ. How we measure

  1. Humor35%
  2. Joy10%
  3. Relief10%

AI estimate · no viewer votes yet

How we measure

AI estimate

Share of emotional signal, not the percentage of people or a probability of enjoyment.

Each viewer contributes one response, split equally across their selected emotions. When available, an automated estimate supplies a prior that is blended with those responses. Counts include distinct viewers, not automated estimates or archived anonymous votes. Fewer than 3 viewers is an early estimate; more responses do not guarantee certainty.

Why it feels this way

The strongest emotional signals are Humor, Excitement, Satisfaction. Genres: Comedy. AI estimate.

Is it worth watching?

Consider this title if you are looking for Humor, Excitement and Satisfaction. Its IMDb rating of 7.5/10 suggests a generally positive audience reception. For these leading emotions, its Feel Score is 74/100.

How did it make you feel?

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Emotional journey

AI · from subtitles
  • Satisfaction
  • Tension
  • Humor

Not enough subtitle evidence

No dominant emotion

Dominant emotion: Curiosity

Dominant emotion: Humor

Dominant emotion: Tension

Dominant emotion: Sympathy

Dominant emotion: Satisfaction

Satisfaction
Tension
Humor
Emotional journey Emotional intensity over the film’s runtime, from quieter to stronger on a fixed 0–1 scale. Hatched intervals have insufficient subtitle evidence. The table provides the values.
Ending hidden

Dominant emotion

Intensity dips around 3 %, then peaks around 98 %.Ending hidden

Emotional journey
%Approximate minuteDominant emotionOverall intensitySatisfactionTensionHumor
2.5 %≈ 3′Curiosity23 %12 %3 %17 %
7.5 %≈ 9′Humor38 %10 %17 %29 %
12.5 %≈ 15′Tension50 %4 %35 %29 %
17.5 %≈ 20′Curiosity50 %3 %33 %26 %
22.5 %≈ 26′Humor49 %10 %21 %40 %
27.5 %≈ 32′Humor54 %13 %25 %40 %
32.5 %≈ 38′Sympathy56 %8 %34 %29 %
37.5 %≈ 44′Humor56 %5 %31 %31 %
42.5 %≈ 49′Sympathy59 %4 %30 %25 %
47.5 %≈ 55′Sympathy55 %9 %29 %19 %
52.5 %≈ 61′Curiosity49 %15 %26 %30 %
57.5 %≈ 67′Sympathy50 %11 %35 %35 %
62.5 %≈ 73′Tension56 %6 %45 %25 %
67.5 %≈ 78′Sympathy60 %6 %43 %16 %
72.5 %≈ 84′Sympathy56 %10 %31 %25 %
77.5 %≈ 90′Humor55 %14 %32 %41 %
82.5 %≈ 96′Tension60 %18 %48 %40 %
87.5 %≈ 102′Tension66 %31 %59 %25 %
92.5 %≈ 107′Satisfaction74 %55 %56 %23 %
97.5 %≈ 113′Satisfaction77 %68 %42 %32 %
Man in a hole

Rags to riches: The emotional tone rises from negative to positive.

Riches to rags: The emotional tone falls from positive to negative.

Man in a hole: The tone falls, then recovers.

Icarus: The tone rises, then falls.

Cinderella: The tone rises, falls, then rises again.

Oedipus: The tone falls, rises, then falls again.

AI reading of the film’s English subtitles (dialogue and sound cues) — not viewer votes. How we measure ↗

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Afterward Reveal viewer responses · may contain spoilers

Viewer responses about feelings after the title ended, separate from feelings while watching. No AI estimates.

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Cast

Dan Aykroyd

Louis Winthorpe III

KH
Kristin Holby

Paul Gleason

Clarence Beeks

Frank Oz

Corrupt Cop

AD
Alfred Drake

Jim Belushi

Harvey

BD
Bo Diddley

AF
Al Franken

Baggage Handler #1

TD
Tom Davis

Baggage Handler #2

MW
Maurice Woods

Duke & Duke Employee

RD
Richard D. Fisher, Jr.

Duke & Duke Employee

AD
Anthony DiSabatino

Duke & Duke Employee

BB
Bonnie Behrend

Duke & Duke Employee

SM
Sunnie Merrill

Duke & Duke Employee

JN
James Newell

Duke & Duke Employee

Details

Directed by
John Landis
Type
Movies
Released
1983
Runtime
116 min
Country
United States of America
Genres
Comedy
Ratings
★ IMDb 7.5 · 185,164 ratings
Feels mostly
Humor
Data updated

Where to watch

Data: JustWatch · Wikidata

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Emotion overlap shows mood similarity, not a prediction of enjoyment.