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Credible Threat: Attacks Against Women Online and the Future of Democracy
Abstract
This book argues that the rampant hate-filled attacks against women online are best understood as patterned resistance to women’s political voice and visibility. This abuse and harassment coalesces into an often-unrecognized form of gender inequality that constrains women’s use of digital public spaces, much as the pervasive threat of sexual intimidation and violence constrain women’s freedom and comfort in physical public spaces. What’s more, the abuse exacerbates inequality among women, those from racial, ethnic, religious, and/or other minority groups, are disproportionately targeted. Drawing on in-depth interviews with women who have been on the receiving end of digital hate, Credible Threat shows that the onslaught of epithets and stereotypes, rape threats, and unsolicited commentary about their physical appearance and sexual desirability come at great professional, personal, and psychological costs for the women targeted—and also with underexplored societal level costs that demand attention. When effective, identity-based attacks undermine women’s contributions to public discourse, create a climate of self-censorship, and at times, push women out of digital publics altogether. Given the uneven distribution of toxicity, those women whose voices are already most underrepresented (e.g., women in male-dominated fields, those from historically undervalued groups) are particularly at risk. In the end, identity-based attacks online erode civil liberties, diminish public discourse, limit the knowledge we have to inform policy and electoral decision making, and teach all women that activism and public service are unappealing, high-risk endeavors to be avoided.
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Pintak, L., Albright, J., Bowe, B. J., et al. (2019) · doi:10.35650/md.2006.a.2019 · Cited by 18
“Genderless” Online Discourse in the 1970s: Muted Group Theory in Early Social Computing
Korn, J. U. (2015) · doi:10.1145/2809523.2809538 · Cited by 13
DEEDS DONE IN DIFFERENT WORDS: A GENRE-BASED APPROACH TO THIRD PARTY PRESIDENTIAL CAMPAIGN DISCOURSE
Neville-Shepard, R. (2011) · KU ScholarWorks (The University of Kansas) · Cited by 12
7 Gender and Race in the Digital Town Hall: Identity-Based Attacks Against US Legislators on Twitter
Sobieraj, S., & Merchant, S. (2022) · doi:10.2478/9788366675612-008 · Cited by 12
Self-citationEzzy, D. (2010) · Taylor & Francis eBooks · doi:10.4324/9780203300084_chapter_3 · Cited by 10
Flagged first, then by citations
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Cited by
Sorted by citations
Earl, J. (2022) · Science Advances · doi:10.1126/sciadv.abl8198 · Cited by 250
Morally Motivated Networked Harassment as Normative Reinforcement
Marwick, A. E. (2021) · Social Media + Society · doi:10.1177/20563051211021378 · Cited by 185
Interrogating the “incel menace”: assessing the threat of male supremacy in terrorism studies
DeCook, J. R., & Kelly, M. (2022) · Critical Studies on Terrorism · doi:10.1080/17539153.2021.2005099 · Cited by 89
Mainstreaming the Blackpill: Understanding the Incel Community on TikTok
Solea, A. I., & Sugiura, L. (2023) · European Journal on Criminal Policy and Research · doi:10.1007/s10610-023-09559-5 · Cited by 105
Metadata
- Authors
- Sobieraj, S.
- Affiliations
- Tufts University (US)
- Corresponding author
- Sobieraj, Sarah
- ORCID
- Sobieraj, Sarah
- Publisher
- Oxford University PressNew York
- Published
- 2020-09-17
- OpenAlex
- W4250715333
- Cited by
- 100
- References
- 146
- Citations by year
- 2026: 20 · 2025: 23 · 2024: 16 · 2023: 18 · 2022: 15 · 2021: 8
- FWCI
- 10.29
- Type
- book
- Language
- en
- Open access
- closed
- Topics
- Social Sciences › Gender Studies › Gender, Feminism, and Media
- Social Sciences › Sociology and Political Science › Stalking, Cyberstalking, and Harassment
- Social Sciences › Gender Studies › Gender Politics and Representation
- Keywords
- online harassment, hate speech, women, gender inequality, digital public space, self-censorship, sexual intimidation, intersectionality, minority women, online abuse, civil liberties, public discourse, women in male-dominated fields
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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.
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