Data Story

The Auteur’s Fingerprint

Fingerprint ridges encode a director’s repeating genres and collaborators — a signature you can see and feel.

filmimdbtmdbdirectorsgenrescollaboratorssignature
Dataset scope
300
directors
14
max films
552
max collabs
Genres
ridges
Each fingerprint turns film count into rings, collaborator density into ridge noise, and dominant genres into ink hue.
Loading fingerprint data
Hypothesis

Directors with more consistent signature patterns (genre + collaborator repetition) are more likely to accumulate recognition and sustained audience trust.

Question: Do directors with consistent “signatures” (genre + collaborator patterns) achieve higher awards or popularity?

Method: Compute a signature profile per director using genre variety and collaborator density; compare consistency proxies across the dataset.

Prediction: Directors with higher film counts and lower signature variety form a distinct band of strong, readable signatures.

Test: Compare signature consistency metrics across director quartiles by film count and collaborator density.

Narrative Arc
Act I

Each director is stamped as a fingerprint — a visual signature built from their filmography.

Act II

Repeated genres and collaborators deepen grooves, thickening the ridges into a recognizable pattern.

Act III

Strong signatures stand out: low entropy, high repetition — the shape of an auteur.

Datasets
  • imdb.film_crew
  • imdb.film_genres
  • imdb.genres
  • imdb.person_collaborations
  • imdb.films
  • tmdb.movies
  • 11_auteurs_fingerprint.json
Limitations
  • Genres are aggregated tags, not weighted by screen time or narrative emphasis.
  • Collaborator counts reflect dataset coverage, which may be incomplete across eras.
  • Film counts are within the dataset, not complete filmographies.
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