Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 23, December 2021

A Personality Prediction Method of WEIBO Users based on Personality Lexicon


Yuanyuan Feng and Kejian Liu, Xihua University, China


Personality is the dominant factor affecting human behavior. With the rise of social network platforms, increasing attention has been paid to predict personality traits by analyzing users' behavior information, and pay little attention to the text contents, making it insufficient to explain personality from the perspective of texts. Therefore, in this paper, we propose a personality prediction method based on personality lexicon. Firstly, we extract keywords from texts, and use word embedding techniques to construct a Chinese personality lexicon. Based on the lexicon, we analyze the correlation between personality traits and different semantic categories of words, and extract the semantic features of the texts posted by Weibo users to construct personality prediction models using classification algorithm. The final experiments shows that compared with SC-LIWC, the personality lexicon constructed in this paper can achieve a better performance.


Personality Lexicon, Machine Learning, Personality Prediction.