Title:	Online Commenting Behavior in Relation To Posts: A Gendered Approach
DNr:	LiU-gpu-2026-5
Project Type:	LiU
Principal Investigator:	Sabrina Mai <sabrina.mai@liu.se>
Affiliation:	Linköpings universitet
Duration:	2026-04-07 – 2026-07-01
Classification:	50401
Keywords:

Abstract

Previous studies on online commenting behavior that have focused on gender primarily study the comments as isolated corpuses, with little attention to the original post itself. As commenting behavior is an interaction that is made in relation to the original post and its author, this study aims to examine how commenting behavior manifests and changes based on attributes of the author, primarily their gender, and their posted content. This study will utilize natural language processing (NLP) techniques to examine the content and sentiment of up to 25 million posts and comments made on social media, along with how topics within the comments "drift" from the topics presented within the original post. A key aim is to test hypotheses on whether there are significant differences in comments based on the gender and roles (e.g. politicians, public figures, and general users) of the original posters.