Analysis of gender sentiment expression in network based on TF-LDA algorithm

Abstract

With the popularity of networks, social media has become an important way to spread gender awareness, in which sentiment expressions can especially reflect the development of feminism and public opinion atmosphere. The team took two of the hottest gender-related news events in 2022 and used crawler technology to collect network data of Weibo comments. Then, we used the TF-LDA model combined with the TF-IDF algorithm and LDA topic model, to screen the keywords respectively, then built a new text based on the filtered results, and made sentiment analysis based on the BosonNLP sentiment lexicons.