社交媒体用户自我表露的影响因素分析

Abstract

选择社交媒体用户作为自我表露的研究对象，基于社会信息加工模型、线索减少理论和去个性化的社会认同模型三个理论，编制量表，研究社交媒体环境下用户的自我表露现状。根据因子分析结果，将自我表露内容分为社会属性信息、兴趣日常、学习工作、态度观点、个人性格和个人隐私信息6个维度。并将社交媒体用户人口统计特征作为自变量，探索其对自我表露的影响。研究发现，女性更倾向于自我表露，同时受教育程度对自我表露程度也有显著影响。

Social media users’self-disclosure is studied in this article. Scale is developed based on Social Information Model (SIM),Reducing Clue Theory (RCT) and Social Identity Model of Deindividuation Effects (SIDE),to explore the status of users’self-disclosure in social media. Self-disclosure can be divided into 6 dimensions built on factor analysis,they are information on social property,daily interest,study and work, attitude, personality and personal privacy. Demographics of social media users is used as independent variable to explore its impact on self-disclosure. We found that women are more inclined to disclose themselves online, while the level of education also has a significant effect on the degree of self-disclosure.