The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
Understanding Social Media Disclosures of Sexual Abuse Through the Lenses of Support Seeking and Anonymity
Abstract
Support seeking in stigmatized contexts is useful when the discloser receives the desired response, but it also entails social risks. Thus, people do not always disclose or seek support when they need it. One such stigmatized context for support seeking is sexual abuse. In this paper, we use mixed methods to understand abuse-related posts on reddit. First, we take a qualitative approach to understand post content. Then we use quantitative methods to investigate the use of "throwaway" accounts, which provide greater anonymity, and report on factors associated with support seeking and first-time disclosures. In addition to significant linguistic differences between throwaway and identified accounts, we find that those using throwaway accounts are significantly more likely to engage in seeking support. We also find that men are significantly more likely to use throwaway accounts when posting about sexual abuse. Results suggest that subreddit moderators and members who wish to provide support pay attention to throwaway accounts, and we discuss the importance of context-specific anonymity in support seeking.
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“Due to its pseudonymous nature, Reddit is a place where users can disclose sensitive and stigmatized topics [15, 36].”
From Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives (2026) · cites this paper as [15]
In the citing paper
“Over 80% of US adults use social media daily [20], placing it ahead of texting, email, and instant messaging, and disclose considerably more about themselves online than offline [21,22].”
From Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media (2020) · cites this paper as [21]
In the citing paper
“With the wide adoption of web and social media technologies, support seeking (and providing) is increasingly happening online and has been shown to be efficacious [21,59].”
From Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media (2020) · cites this paper as [21]
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Governance of Social Media Platforms: A Literature Review
Kumar, A., & Gupta, S. (2023) · Pacific Asia journal of the Association for Information Systems · doi:10.17705/1pais.15103 · Cited by 14
Mitigating Barriers to Public Social Interaction with Meronymous Communication
Soliman, N., Kang, H. B., Latzke, M., Bragg, J., Chang, J. C., Zhang, A. X., & Karger, D. R. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642241 · Cited by 16
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Li, Z., Zhu, Z., Gui, X., & Luo, Y. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103555 · Cited by 19
Self-disclosure and Response Behaviors in Socially Stigmatized Contexts on Social Media
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Self-citation
Metadata
- Authors
- Andalibi, N., Haimson, O. L., De Choudhury, M., & Forte, A.
- Affiliations
- Drexel University (US)
- University of California, Irvine (US)
- Georgia Institute of Technology, Atlanta, GA, USA
- Venue
- Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2016-05-07
- Pages
- 3906-3918
- OpenAlex
- W2399480376
- Cited by
- 378
- References
- 62
- Citations by year
- 2026: 24 · 2025: 35 · 2024: 44 · 2023: 45 · 2022: 51 · 2021: 52 · 2020: 42 · 2019: 31 · 2018: 28 · 2017: 20 · 2016: 6
- FWCI
- 254.82
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Social Sciences › Gender Studies › Sexual Assault and Victimization Studies
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Psychology › Clinical Psychology › Child Abuse and Trauma
- Keywords
- sexual abuse, online self-disclosure, support seeking, anonymity, Reddit, stigma, gender differences
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.
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