Abstract

Reddit’s men’s rights community (/r/MensRights) has been criticized for the promotion of misogynistic language, toxic masculinity and discourses that reinforce alt-right ideologies. Conversely, the men’s liberation (/r/MensLib) community integrates inclusive politics, intersectionality and masculinity within a broad umbrella of self-reflection that suggests toxic masculinity harms men as well as women.

We use machine learning text classifiers, keyword frequencies, and qualitative approaches first to distinguish these two subreddits, and second to interpret the differences ideologically rather than topically. We further integrate platform metadata (referred to as ‘platform signals’) to distinguish the subreddits. These signals help us understand how similar terms can be used to arrive at different interpretations of gender and discrimination. Where /r/MensLib tends to see masculinity as an adjective and women as peers, /r/MensRights views being a man as an essential quality, men as the target of discrimination, and women as sources of personalized grievances.