分析主角亲和力与能力如何影响电影评分，发现影响较小但存在性别差异。
What makes for an enjoyable protagonist? An analysis of character warmth and competence
- 用AI工具量化主角亲和力与能力，基于2858部影视作品分析
- 亲和力与能力对评分有微弱正向影响，男性主角更受青睐且评分更高
- 适合研究影视角色心理学、内容推荐系统或生成式AI应用者
基于心理学与文学理论，我们探究了电影主角的亲和力与能力是否能预测IMDb评分，以及这种关系在不同类型片中是否存在差异。利用来自电影剧本语料库的2,858部影视作品，通过AI辅助标注识别主角，并使用LLM_annotate工具量化其亲和力与能力（人类与LLM一致性：r = .83）。预注册的贝叶斯回归分析显示，亲和力与能力均与观众评分存在理论一致但微弱的正相关，而类型特异性交互项并未显著提升预测效果。男性主角略低于女性主角的亲和力水平，且以男性为主角的影片平均评分更高（该效应强度是亲和力/能力与评分关联的数倍）。结果表明，尽管观众偏好温暖、有能力的角色，但其对电影评分的影响有限，说明角色性格只是影响评分的众多因素之一。使用LLM_annotate与gpt-4.1-mini进行的AI辅助标注在大规模分析中表现有效，但偶尔仍不及人工标注质量。
原文摘要 · Abstract (English)
Drawing on psychological and literary theory, we investigated whether the warmth and competence of movie protagonists predict IMDb ratings, and whether these effects vary across genres. Using 2,858 films and series from the Movie Scripts Corpus, we identified protagonists via AI-assisted annotation and quantified their warmth and competence with the LLM_annotate package ([1]; human-LLM agreement: r = .83). Preregistered Bayesian regression analyses revealed theory-consistent but small associations between both warmth and competence and audience ratings, while genre-specific interactions did not meaningfully improve predictions. Male protagonists were slightly less warm than female protagonists, and movies with male leads received higher ratings on average (an association that was multiple times stronger than the relationships between movie ratings and warmth/competence). These findings suggest that, although audiences tend to favor warm, competent characters, the effects on movie evaluations are modest, indicating that character personality is only one of many factors shaping movie ratings. AI-assisted annotation with LLM_annotate and gpt-4.1-mini proved effective for large-scale analyses but occasionally fell short of manually generated annotations.
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