{"schema":"record/v1","id":"art_01M5NNY159CEG909GAVQZDWECZ","type":"article","revision":1,"etag":"\"r1.s0\"","title":"How can I produce one comparable distinctiveness score per character, and what does the score actually measure?","summary":"Seła et al. (arXiv v1, 2023) define a character's distinctiveness as the degree to which their speech differs from the other characters in the same play and measure it two ways: median bootstrap energy distance between the character's character-3-gram distribution and everyone else's (statistically stronger), and the area under the curve of a character's 100 top weighted-log-odds keywords (more interpretable). Applied to 3301 characters in 2324 works (DraCor: French, German, Russian, Shakespeare), the score is largely driven by dialect, accent, class markers and topic, and falls as a character's share of dialogue rises. It is a within-play statistic, not a quality score.","status":"active","body":{"text":"Seła et al. (arXiv v1, 2023) define a character's distinctiveness as the degree to which their speech differs from the other characters in the same play and measure it two ways: median bootstrap energy distance between the character's character-3-gram distribution and everyone else's (statistically stronger), and the area under the curve of a character's 100 top weighted-log-odds keywords (more interpretable). Applied to 3301 characters in 2324 works (DraCor: French, German, Russian, Shakespeare), the score is largely driven by dialect, accent, class markers and topic, and falls as a character's share of dialogue rises. It is a within-play statistic, not a quality score.\n\nCurator qualifications: Verified the corpus size and the two measures. The note that the protocol needs 2000 words and language-specific corpora is the producer's labelled synthesis.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2301.05659v1","note":"abstract/methods"},{"url":"https://zenodo.org/api/records/7383687","note":"abstract/methods"}]},"categories":["T01","T20"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://arxiv.org/abs/2301.05659v1","claim":"Seła et al. 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(arXiv v1, 2023) define a character's distinctiveness as the degree to which their speech differs from the other characters in the same play and measure it two ways: median bootstrap energy distance between the character's character-3-gram distribution and everyone else's (statistically stronger), and the area under the curve of a character's 100 top weighted-log-odds keywords (more interpretable). Applied to 3301 characters in 2324 works (DraCor: French, German, Russian, Shakespeare), the score is largely driven by dialect, accent, class markers and topic, and falls as a character's share of dialogue rises. It is a within-play statistic, not a quality score.\n\nCurator qualifications: Verified the corpus size and the two measures. The note that the protocol needs 2000 words and language-specific corpora is the producer's labelled synthesis.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2301.05659v1","note":"abstract/methods"},{"url":"https://zenodo.org/api/records/7383687","note":"abstract/methods"}]},"tags":[],"type":"article","links":[],"title":"How can I produce one comparable distinctiveness score per character, and what does the score actually measure?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"Seła et al. (arXiv v1, 2023) define a character's distinctiveness as the degree to which their speech differs from the other characters in the same play and measure it two ways: median bootstrap energy distance between the character's character-3-gram distribution and everyone else's (statistically stronger), and the area under the curve of a character's 100 top weighted-log-odds keywords (more interpretable). Applied to 3301 characters in 2324 works (DraCor: French, German, Russian, Shakespeare), the score is largely driven by dialect, accent, class markers and topic, and falls as a character's share of dialogue rises. It is a within-play statistic, not a quality score.","evidence":{"claims":[{"url":"https://arxiv.org/abs/2301.05659v1","claim":"Seła et al. 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