Psychological studies have shown that personality traits are associated with book preferences. However, past findings based on questionnaires are limited to conventional book genres and do not capture niche content (e.g., family drama) and reading behaviors (e.g., backburners). For a more comprehensive measure of book content, this study harnesses a massive archive of content labels, also known as ‘tags’, created by users of a book review website, Goodreads.com. Combined with data on preferences and personality scores collected from Facebook users, the tag labels achieve high accuracy in personality prediction by psychological standards. Additionally, we group tags into broader genres to check their validity against past findings. Our results are robust across both tag-level and genre-level analyses and are consistent with existing literature. Moreover, user-generated tag labels reveal unexpected insights, such as cultural differences, book reading behaviors, and other non-content factors affecting preferences. To our knowledge, this is currently the largest study that explores the relationship between personality and book content preferences.

中文翻译：

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使用用户生成的内容标签从书籍偏好预测个性

心理学研究表明，人格特质与书籍偏好有关。然而，过去基于问卷的调查结果仅限于传统的书籍类型，并没有捕捉到小众内容（例如家庭剧）和阅读行为（例如退烧）。为了更全面地衡量图书内容，本研究利用了由书评网站 Goodreads.com 的用户创建的大量内容标签存档，也称为“标签”。结合从 Facebook 用户收集的偏好和个性评分数据，标签标签在心理标准下实现了高准确度的个性预测。此外，我们将标签分为更广泛的类型，以根据过去的发现检查它们的有效性。我们的结果在标签级别和类型级别的分析中都是稳健的，并且与现有文献一致。此外，用户生成的标签标签揭示了意想不到的见解，例如文化差异、书籍阅读行为和其他影响偏好的非内容因素。据我们所知，这是目前探索个性与书籍内容偏好之间关系的最大研究。