feeldb

Bounty Hunters

2016 · 106 min · Director: Shin Tae-ra, Shin Terra ★ IMDb 5.4 · 1,251 ratings

Show plot summary (may contain spoilers)

It is the story of five bounty hunters who chase fugitives for money in China, Hong Kong, Korea and Thailand.

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Emotional fingerprint

Bounty Hunters (2016) — Movie. Top emotional signals: Excitement 32%, Humor 28%, Surprise 15%. Source: AI estimate. Shares describe emotional signal, not percentages of people. Your experience may differ. How we measure

  1. Humor28%
  2. Love15%
  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 Excitement, Humor, Surprise. Genres: Comedy, Romance, Action. AI estimate.

Is it worth watching?

Consider this title if you are looking for Excitement, Humor and Surprise. Its IMDb rating of 5.4/10 suggests a mixed audience reception; consider how well the emotional profile suits you. For these leading emotions, its Feel Score is 61/100.

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Emotional journey

AI · from subtitles
  • Tension
  • Excitement
  • Relief

Not enough subtitle evidence

No dominant emotion

Dominant emotion: Humor

Dominant emotion: Tension

Dominant emotion: Excitement

Dominant emotion: Sympathy

Dominant emotion: Relief

Tension
Excitement
Relief
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. Not enough subtitle evidence
Ending hidden

Dominant emotion

Intensity dips around 3 %, then dips around 23 %, then peaks around 83 %.Ending hidden

Emotional journey
%Approximate minuteDominant emotionOverall intensityTensionExcitementRelief
2.5 %≈ 3′Humor50 %37 %23 %3 %
7.5 %≈ 8′Tension57 %53 %33 %4 %
12.5 %≈ 13′Tension59 %57 %36 %8 %
17.5 %≈ 19′Humor53 %41 %24 %9 %
22.5 %≈ 24′Humor50 %29 %16 %5 %
27.5 %≈ 29′Humor51 %36 %26 %4 %
32.5 %≈ 34′Excitement60 %55 %44 %10 %
37.5 %≈ 40′Tension66 %55 %41 %20 %
42.5 %≈ 45′Sympathy61 %40 %28 %21 %
47.5 %≈ 50′Tension57 %44 %31 %13 %
52.5 %≈ 56′Humor61 %57 %34 %9 %
57.5 %≈ 61′Tension73 %71 %34 %8 %
62.5 %≈ 66′Tension76 %75 %40 %13 %
67.5 %≈ 72′Relief70 %68 %41 %24 %
72.5 %≈ 77′Tension69 %68 %41 %20 %
77.5 %≈ 82′Tension73 %73 %48 %15 %
82.5 %≈ 87′Tension80 %80 %57 %26 %
87.5 %≈ 93′Tension80 %69 %54 %44 %
92.5 %≈ 98′Relief72 %42 %38 %55 %
97.5 %≈ 103′Not enough subtitle evidenceNot enough subtitle evidenceNot enough subtitle evidenceNot enough subtitle evidenceNot enough subtitle evidence
Cinderella

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 ↗

Kadri — your film companion

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

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Cast

YT
Yan Tang

TY
Tang Yan

Wonder Woman Cat

KN
Karena Ng Chin-Yu

Swan

LF
Louis Fan Siu-Wong

Baobao / "Babe" / "Bobo"

XZ
Xu Zhengxi

Tommy

KM
Kim Min-kyo

Eom Sam

HB
Hwang Bo-ra

Chairman's entourage / Cat stand-in

LK
Lee Kyu-ho

Eom Sam's subordinate

SC
Seo Chong-ju

Tommy's Subordinate

KS
Kim Seung-pil

Hong Kong Hunter

Details

Directed by
Shin Tae-ra, Shin Terra
Written by
Edmond Wong, Shin Terra
Type
Movies
Released
2016
Runtime
106 min
Country
China, South Korea, Hong Kong
Ratings
★ IMDb 5.4 · 1,251 ratings
Feels mostly
Excitement
Data updated

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