Logo image
Understanding Social Media Disclosures of Sexual Abuse Through the Lenses of Support Seeking and Anonymity
Conference proceeding

Understanding Social Media Disclosures of Sexual Abuse Through the Lenses of Support Seeking and Anonymity

Nazanin Andalibi, Oliver L. Haimson, Munmun De Choudhury, Andrea Forte and ACM
34TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2016, pp 3906-3918
01 Jan 2016

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Software Engineering Computer Science, Theory & Methods Science & Technology Technology
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.

Metrics

11 Record Views
321 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Software Engineering
Computer Science, Theory & Methods
Logo image