近日，实验室博士生朱浩浩关于文本人格检测的研究被自然语言处理领域顶级期刊 IEEE Transactions on Audio, Speech, and Language Processing (TASLP) 录用。TASLP 是中科院一区期刊，中国计算机学会推荐B类期刊，清华推荐A类期刊。

论文题目：Enhancing Textual Personality Detection toward Social Media: Integrating Long-term and Short-term Perspectives

中文题目：增强面向社交媒体的文本人格检测：长期与短期视角的整合

论文摘要：Textual personality detection aims to identify personality characteristics by analyzing user-generated content on social media platforms. Extensive psychological literature highlights that personality encompasses both long-term stable traits and short-term dynamic states. However, existing studies often concentrate only on either long-term or short-term personality representations, neglecting the integration of both aspects. This limitation hinders a comprehensive understanding of individuals' personalities, as both stable traits and dynamic states are vital. To bridge this gap, we propose a Dual Enhanced Network (DEN) to jointly model users' long-term and short-term personality traits. In DEN, the Long-term Personality Encoding module models stable long-term personality traits by analyzing consistent patterns in the usage of psychological entities. The Short-term Personality Encoding module captures dynamic short-term personality states by modeling the contextual information of individual posts in real-time. The Bi-directional Interaction module integrates both aspects of personality, creating a cohesive and comprehensive representation of the user's personality. Experimental results on two personality detection datasets demonstrate the effectiveness of the DEN model and underscore the importance of considering both stable and dynamic aspects of personality in textual personality detection.

中文摘要：文本人格检测旨在通过分析社交媒体平台上用户生成的内容来识别用户的人格特征。大量心理学文献强调，人格既包括长期稳定的特质，也包括短期动态的状态。然而，现有研究往往只关注长期或短期的人格表征，忽略了这两个方面的整合。由于稳定特质和动态状态都至关重要，这种局限性阻碍了对个体人格的全面理解。为了弥补这一差距，我们提出了一种长短期对偶增强网络（DEN），用于联合建模用户的长期和短期人格特质。在DEN中，长期人格编码模块通过分析心理实体使用中的一致模式来建模稳定的长期人格特质。短期人格编码模块通过实时建模单个帖子的上下文信息来捕捉动态的短期人格状态。双向交互模块整合了人格的这两个方面，形成了对用户人格的连贯且全面的表征。在两个人格检测数据集上的实验结果证明了DEN模型的有效性，并强调了在文本人格检测中同时考虑人格的稳定和动态方面的重要性。