Abstract: Personality is a stable construction, which is associated with thoughts, emotions and behaviors of human. Any technology involved in understanding, analyzing and predicting human behaviors may benefit from personality recognition. Accurately recognizing the personality will contribute to the research of human-computer interaction, recommendation system, cyberspace security, etc. Social media provides high-quality data for personality recog-nition, while classic personality measurement methods such as self-report scales and projective tests can no longer match the social media data in the age of big data. Moreover, the current mainstream personality recognition methods based on machine learning still have lots of room for performance improvement. Therefore, this paper investigates the literature on personality recognition based on social media data, introduces the background knowledge of personality recognition and summarizes the research status according to the data types of recognition model input used, specifically based on social text data, social image data, social application data and multimodal data. Finally, this paper proposes seven future research directions of personality recognition based on social media data.

Key words: personality recognition, social media, Big Five model, Myers-Briggs type indicator

摘要： 人格是一种与人类的想法、情绪、行为相关的稳定模式，任何涉及对人类行为进行理解、分析、预测的技术都有可能受益于人格识别。准确识别人格将有助于人机交互、推荐系统、网络空间安全等研究。社交媒体为人格识别研究提供了高质量的数据源，而自陈量表、投射测验等经典人格测量方法已无法匹配大数据时代的社交媒体数据，且主流的基于机器学习训练的人格识别模型仍有很大性能提升空间。故此，梳理了当前面向社交媒体数据的人格识别的研究，介绍了人格识别的背景知识，按照人格识别模型输入数据的类型分别综述研究现状并系统地总结了经典文献，具体类型为基于社交文本数据、基于社交图像数据、基于社交应用统计数据以及基于多模态数据。最后，提出面向社交媒体数据的人格识别研究的七个未来研究方向。

关键词: 人格识别, 社交媒体, 大五人格, 迈尔斯布里格斯类型指标