Using Platform Signals for Distinguishing Discourses: The Case of Men’s Rights and Men’s Liberation on Reddit

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.

Investigating Reddit to detect subreddit and author stereotypes and to evaluate author assortativity

“…Other works, marginally related to our proposal, focus on the study of specific aspects of subreddits or user behaviours. For instance, in LaViolette and Hogan [9], the authors use text classification and computational critical discourse analysis to distinguish and interpret ideological differences between subreddits. In Zhang et al [42], the authors present a study regarding a quantitative, language-based typology of communities' identity, revealing how several social phenomena manifest across communities.…”

“…Authors have analysed and are continuously analysing, many aspects of Reddit, ranging from community structures and interactions [3–5] to user behaviour [6,7], from the analysis of the structure and content of subreddits, posts and comments [8] to the analysis of the structural properties of Reddit when it is seen as a social network [5]. Other specific topics, such as text classification [9], user migration [10], political and ideological aspects [11], have been also studied.…”

Digitally Mediated Misogyny and Critical Discourse Studies: Methodological and Ethical Implications

“…Many scholars have studied the manosphere using computational or quantitative methods such as natural language processing or topic modelling (e.g. Mountford 2018;Rafail and Freitas 2019;LaViolette and Hogan 2019). These approaches have been important for developing an understanding of hate speech within the manosphere, as these methods can enable researchers to automatically detect or determine the presence of "toxic" or misogynistic language within manosphere communities (e.g.…”