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Social Support, Reciprocity, and Anonymity in Responses to Sexual Abuse Disclosures on Social Media
Open accessAbstract
Seeking and providing support is challenging. When people disclose sensitive information, audience responses can substantially impact the discloser's wellbeing. We use mixed methods to understand responses to online sexual abuse-related disclosures on Reddit. We characterize disclosure responses, then investigate relationships between post content, comment content, and anonymity. We illustrate what types of support sought and provided in posts and comments co-occur. We find that posts seeking support receive more comments, and comments from “throwaway” (i.e., anonymous) accounts are more likely on posts also from throwaway accounts. Anonymous commenting enables commenters to share intimate content such as reciprocal disclosures and supportive messages, and commenter anonymity is not associated with aggressive or unsupportive comments. We argue that anonymity is an essential factor in designing social technologies that facilitate support seeking and provision in socially stigmatized contexts, and provide implications for social media site design. CAUTION: This article includes content about sexual abuse.
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“Andalibi et al [66] found that these two kinds of support can co-occur with other forms of support, such as posts seeking ES often seeking esteem and network support, and Attai et al [68] noted that Twitter is effective in seeking and providing health-related informational needs, contextually related with our problem of interest.”
From Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media (2020) · cites this paper as [66]
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“These two forms of support have been found to be most prevalent and effective in several studies of online support and social media [38,62,66,67].”
From Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media (2020) · cites this paper as [66]
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Barta, K., & Andalibi, N. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479574 · Cited by 165
Self-citationReclaiming Stigmatized Narratives
Gallagher, R. J., Stowell, E., Parker, A. G., & Welles, B. F. (2019) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3359198 · Cited by 136
Remember the Human: A Systematic Review of Ethical Considerations in Reddit Research
Fiesler, C., Zimmer, M., Proferes, N., Gilbert, S., & Jones, N. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3633070 · Cited by 113
Metadata
- Authors
- Andalibi, N., Haimson, O. L., Choudhury, M. D., & Forte, A.
- Affiliations
- Drexel University (US)
- University of California, Irvine (US)
- Georgia Institute of Technology (US)
- Venue
- ACM Transactions on Computer-Human Interaction
- Published
- 2018-10
- Volume
- 25
- Issue
- 5
- Pages
- 1-35
- ISSN
- 1073-0516 (ISSN-L)
- 1557-7325
- OpenAlex
- W2894631352
- Cited by
- 200
- References
- 108
- Citations by year
- 2026: 25 · 2025: 32 · 2024: 29 · 2023: 29 · 2022: 25 · 2021: 30 · 2020: 22 · 2019: 6 · 2018: 2
- FWCI
- 34.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Transactions on Computer-Human Interaction (publishedVersion)
- Funders
- National Science Foundation (1253302)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Social Sciences › Gender Studies › Sexual Assault and Victimization Studies
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Keywords
- sexual abuse, disclosure, social support, reciprocity, anonymity, Reddit, social media comments
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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