黑暗人格特质与在线毒性：将自我报告与Reddit活动联系起来
Dark Personality Traits and Online Toxicity: Linking Self-Reports to Reddit Activity
AI总结：
研究探讨了黑暗人格特质与在线行为之间的关系，发现自我报告的不文明互动与黑暗人格特质相关，但计算特征无法可靠预测人格特质。
摘要：
黑暗人格特质长期以来与反社会和有毒的在线行为相关，但其与可观察的在线活动之间的关系仍不清楚。我们调查了经过验证的黑暗人格测量、自我报告的在线不文明经历以及从现实世界用户活动中提取的语言和行为特征之间的关联。为此，我们开发了一个Web应用程序，安全地将通过Amazon Mechanical Turk收集的经过验证的心理学问卷回答与参与者的Reddit活动链接起来。这产生了包含近57,000条评论（220万词）的数据库，来自114名用户，通过广泛的语言和行为特征表示。我们的分析揭示了自我报告行为与观察行为之间的明显区别。黑暗人格特质与自我报告的不文明互动参与有持续关联。然而，没有经过验证的黑暗人格维度显著预测文本衍生的毒性或语言特征。相反，自我报告的参与或被有毒行为针对的经历在用户语言中得到稳健反映，表现出与负面性、道德框架和情绪强度测量的一致关联。这些发现突显了稳定的人格特质与其在表面语言信号中的表现之间的差距。虽然计算特征能够有效捕捉在线不文明行为的参与，但在此框架内，它们无法提供可靠的底层人格构念代理。我们的结果强调了将计算方法建立在经过验证的心理学测量上的重要性，并指出了需要更丰富、上下文感知的表示来更好地理解人格与在线行为之间的关系。
英文摘要：
Dark personality traits have long been associated with antisocial and toxic online behaviors, yet their relationship with observable online activity remains unclear. We investigate the association between validated dark personality measures, self-reported experiences of online incivility, and linguistic and behavioral features extracted from real-world user activity. To this end, we developed a Web application that securely links responses to validated psychological questionnaires collected via Amazon Mechanical Turk with participants' Reddit activity. This yielded a dataset of nearly 57K comments (2.2M tokens) from 114 users, represented through a broad set of linguistic and behavioral features. Our analyses reveal a clear distinction between self-reported and observed behavior. Dark personality traits show consistent associations with self-reported engagement in uncivil interactions. However, no validated dark personality dimension significantly predicts text-derived toxicity or linguistic features. In contrast, self-reported experiences of engaging in or being targeted by toxic behavior are robustly reflected in users' language, exhibiting consistent associations with measures of negativity, moral framing, and emotional intensity. Taken together, these findings highlight a gap between stable personality traits and their manifestation in surface-level linguistic signals. While computational features effectively capture behavioral engagement in online incivility, they do not provide reliable proxies for underlying personality constructs within the present framework. Our results underscore the importance of grounding computational approaches in validated psychological measures and point to the need for richer, context-aware representations to better understand the relationship between personality and online behavior.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
