文本人格检测研究综述

doi:10.11896/jsjkx.240500071

摘要/Abstract

摘要： 文本人格检测是人格计算领域一项重要的研究内容,旨在分析用户生成文本中隐含的人格特质。随着社交网络的发展,人们习惯于在线发布蕴含心理活动的内容,这为文本人格检测提供了新的机遇。准确地检测用户人格特质在心理健康诊断、舆情监控、人机交互系统设计以及大语言模型构建等方面具有重要意义。文中对文本人格检测的相关研究和新颖方法进行了深入调研和全面综述。首先介绍了人格检测相关背景知识、任务模式;其次从心理语言学统计方法、特征工程方法、深度学习方法、预训练语言模型4个方面梳理了现有方法;然后对当前广泛使用的评测数据集及模型效果进行了总结;最后从人格检测的可靠性、公平性、伦理与隐私、数据集和评价指标统一以及大语言模型与人格5个方面分析了本领域存在的问题和未来研究方向。

关键词: 人格计算, 社交网络, 用户生成文档, 大语言模型

Abstract: Text-based personality detection is an important research content in the personality computing field,aiming to analyze the implicit personality traits in user-generated text.With the booming of social networks,people are accustomed to posting online content that implies their psychological activities,which provides new opportunities for text-based personality detection.Accurately detecting personality traits is important in psychological health diagnosis,public opinion monitoring,human-computer interac-tion system design,and even in the construction of large language models today.This paper provides a comprehensive review of text-based personality detection.Firstly,it introduces the background and task patterns of personality detection.Secondly,the existing detection methods are categorized into four aspects:psycholinguistic statistical methods,feature engineering me-thods,deep learning methods,and pre-trained language models.Then,the commonly used datasets and model performance are summarized.Finally,the issues and future research in this field are analyzed from five aspects:reliability,fairness,ethical and privacy,the unification of dataset and evaluation metrics,and the relationship between large language models and personality.

Key words: Personality computing, Social networks, User-generated content, Large language model

中图分类号:

TP391

朱洋甫, 李美玲, 谭嘉辰, 吴斌. 文本人格检测研究综述[J]. 计算机科学, 2024, 51(12): 209-222. https://doi.org/10.11896/jsjkx.240500071

ZHU Yangfu, LI Meiling, TAN Jiachen, WU Bin. Study on Text-based Personality Detection－A Review[J]. Computer Science, 2024, 51(12): 209-222. https://doi.org/10.11896/jsjkx.240500071

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