论文标题
使用电影脚本对虚构字符的MBTI人格预测
MBTI Personality Prediction for Fictional Characters Using Movie Scripts
论文作者
论文摘要
了解故事的NLP模型应该能够理解其中的字符。为了支持为此目的的神经模型的发展，我们构建了一个基准，故事2人格。任务是根据角色的叙述来预测电影角色的MBTI或5个人格类型。实验表明，我们的任务对于现有的文本分类模型具有挑战性，因为没有人能够在很大程度上超越随机猜测。我们进一步提出了一个使用言语和非语言描述的人格预测的多视图模型，与仅使用言语描述相比，该模型可提供改进。我们数据集中的独特性和挑战要求从理解角色的角度来开发叙事理解技术。
An NLP model that understands stories should be able to understand the characters in them. To support the development of neural models for this purpose, we construct a benchmark, Story2Personality. The task is to predict a movie character's MBTI or Big 5 personality types based on the narratives of the character. Experiments show that our task is challenging for the existing text classification models, as none is able to largely outperform random guesses. We further proposed a multi-view model for personality prediction using both verbal and non-verbal descriptions, which gives improvement compared to using only verbal descriptions. The uniqueness and challenges in our dataset call for the development of narrative comprehension techniques from the perspective of understanding characters.
