Gender-Related Differences in Online Comment Sections: Findings From a Large-Scale Content Analysis of Commenting Behavior

Comment sections below news articles are public fora in which potentially everyone can engage equal and fair discussions on political social issues. Yet, empirical studies have reported that many comment spaces of selective participation, discrimination, verbal abuse. The current study complements these findings by analyzing gender-related differences participation incivility. It uses a sample 303,342 user comments from 14 German media Facebook pages. We compare rates female male users as well associations between the users’ gender, incivility their comments, adjacent replies. To determine we developed Supervised Machine Learning Model (classifier) using pre-trained word embeddings word// frequency features. show that, overall, women participate less than men. Comments written authors more civil authors. Women’s do not receive uncivil replies men’s punished disproportionately for communicating uncivilly. These contribute to discourse online provide insights into dynamics discussions.