Jai Aggarwal
2024
Style-Shifting Behaviour of the Manosphere on Reddit
Jai Aggarwal
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Suzanne Stevenson
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Hate speech groups (HSGs) may negatively influence online platforms through their distinctive language, which may affect the tone and topics of other spaces if spread beyond the HSGs. We explore the linguistic style of the Manosphere, a misogynistic HSG, on Reddit. We find that Manospheric authors have a distinct linguistic style using not only uncivil language, but a greater focus on gendered topics, which are retained when posting in other communities. Thus, potentially harmful aspects of Manospheric style carry over into posts on non-Manospheric subreddits, motivating future work to explore how this stylistic spillover may negatively influence community health.
2023
Investigating Online Community Engagement through Stancetaking
Jai Aggarwal
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Brian Diep
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Julia Watson
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Suzanne Stevenson
Findings of the Association for Computational Linguistics: EMNLP 2023
Much work has explored lexical and semantic variation in online communities, and drawn connections to community identity and user engagement patterns. Communities also express identity through the sociolinguistic concept of stancetaking. Large-scale computational work on stancetaking has explored community similarities in their preferences for stance markers – words that serve to indicate aspects of a speaker’s stance – without considering the stance-relevant properties of the contexts in which stance markers are used. We propose representations of stance contexts for 1798 Reddit communities and show how they capture community identity patterns distinct from textual or marker similarity measures. We also relate our stance context representations to broader inter- and intra-community engagement patterns, including cross-community posting patterns and social network properties of communities. Our findings highlight the strengths of using rich properties of stance as a way of revealing community identity and engagement patterns in online multi-community spaces.
2020
Exploration of Gender Differences in COVID-19 Discourse on Reddit
Jai Aggarwal
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Ella Rabinovich
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Suzanne Stevenson
Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020
Decades of research on differences in the language of men and women have established postulates about the nature of lexical, topical, and emotional preferences between the two genders, along with their sociological underpinnings. Using a novel dataset of male and female linguistic productions collected from the Reddit discussion platform, we further confirm existing assumptions about gender-linked affective distinctions, and demonstrate that these distinctions are amplified in social media postings involving emotionally-charged discourse related to COVID-19. Our analysis also confirms considerable differences in topical preferences between male and female authors in pandemic-related discussions.
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