DOI:10.6129/CJP.201909_61(3).0003
Chinese Journal of Psychology 2019, Vol.61, No.3, 209-230

A Text Analysis Approach to Analyzing Gender Differences in Breakup Posts on Social Media

Lee-Xieng Yang（Department of Psychology, National Chengchi University；Research Center for Mind, Brain, and Learning, National Chengchi University）；Ching-Fan Sheu（Institute of Education, National Cheng-Kung University）

Abstract

Two approaches to text analysis have been applied in the current work to investigate gender differences in breakup posts on social media in Taiwan. First, we calculated the probabilities of the types of words, such as personal pronoun and other word categories based on the Chinese Linguistic Inquiry and Word Count(LIWC), occurring in the posts to predict author’s gender. The results showed that personal pronoun outperformed other word types at predicting gender for social media break-up posts. Second, we conducted stylometric analysis on these posts to extract keywords for different gender. The occurring probabilities of these keywords were then used to predict the author’s gender of the post. The results showed that including keywords in the top one percent as predictors enabled a model to perform better than the first approach. A network analysis was carried out, respectively, for each gender to examine the psychological and linguistic features of these keywords and their relationship with reference to the Chinese LIWC. The typical features, defined in terms of the centrality indices, such as word types of verb, adverb, relative, social process, biological process and cognitive mechanism were found to be common for both gender. However, features of affection words, sexual words, and negate words showed up only for breakup posts authored by females. We conclude that among Taiwanese users of social media females were more likely than males to make affective statements.

Keywords: gender differences, social media, stylometric analysis, text analysis