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Victim-Centred Abuse Investigations and Defenses for Social Media Platforms

Zaid Hakami, Ashfaq Ali Shafin, Peter J. Clarke, Niki Pissinou, Bogdan Carbunar

TL;DR

This work investigates online abuse targeting minority-serving university students, highlighting substantial, high-impact experiences across multiple platforms. Using a mixed-methods approach with a $n = 230$ survey and $n = 15$ interviews, the authors derive design requirements for abuse defenses and propose ARI, a unified, transparent, and personalized defense blueprint that crowdsources abuse verification and links abuser data to funding. Key contributions include documentation of cross-platform abuse patterns, nuanced preferences for platform responses, and a costs-and-certification model aimed at sustainable defense. The study demonstrates the need to balance privacy, anonymity, and accountability while enabling victims to obtain timely, evidence-backed support from platforms. ARI represents a pragmatic path toward victim-centered moderation that can enhance safety and trust on social platforms.

Abstract

Online abuse, a persistent aspect of social platform interactions, impacts user well-being and exposes flaws in platform designs that include insufficient detection efforts and inadequate victim protection measures. Ensuring safety in platform interactions requires the integration of victim perspectives in the design of abuse detection and response systems. In this paper, we conduct surveys (n = 230) and semi-structured interviews (n = 15) with students at a minority-serving institution in the US, to explore their experiences with abuse on a variety of social platforms, their defense strategies, and their recommendations for social platforms to improve abuse responses. We build on study findings to propose design requirements for abuse defense systems and discuss the role of privacy, anonymity, and abuse attribution requirements in their implementation. We introduce ARI, a blueprint for a unified, transparent, and personalized abuse response system for social platforms that sustainably detects abuse by leveraging the expertise of platform users, incentivized with proceeds obtained from abusers.

Victim-Centred Abuse Investigations and Defenses for Social Media Platforms

TL;DR

This work investigates online abuse targeting minority-serving university students, highlighting substantial, high-impact experiences across multiple platforms. Using a mixed-methods approach with a survey and interviews, the authors derive design requirements for abuse defenses and propose ARI, a unified, transparent, and personalized defense blueprint that crowdsources abuse verification and links abuser data to funding. Key contributions include documentation of cross-platform abuse patterns, nuanced preferences for platform responses, and a costs-and-certification model aimed at sustainable defense. The study demonstrates the need to balance privacy, anonymity, and accountability while enabling victims to obtain timely, evidence-backed support from platforms. ARI represents a pragmatic path toward victim-centered moderation that can enhance safety and trust on social platforms.

Abstract

Online abuse, a persistent aspect of social platform interactions, impacts user well-being and exposes flaws in platform designs that include insufficient detection efforts and inadequate victim protection measures. Ensuring safety in platform interactions requires the integration of victim perspectives in the design of abuse detection and response systems. In this paper, we conduct surveys (n = 230) and semi-structured interviews (n = 15) with students at a minority-serving institution in the US, to explore their experiences with abuse on a variety of social platforms, their defense strategies, and their recommendations for social platforms to improve abuse responses. We build on study findings to propose design requirements for abuse defense systems and discuss the role of privacy, anonymity, and abuse attribution requirements in their implementation. We introduce ARI, a blueprint for a unified, transparent, and personalized abuse response system for social platforms that sustainably detects abuse by leveraging the expertise of platform users, incentivized with proceeds obtained from abusers.

Paper Structure

This paper contains 27 sections, 3 figures, 2 tables.

Figures (3)

  • Figure 1: (a) Gender-based distribution of the social platforms rated top-3 most used by survey respondents. (b) Platforms where survey respondents were exposed to most abusive messages. Discord is the least frequently mentioned top-3 platform but ranks third on user exposure to abusive messages. Respondents experienced abusive messages with impact above 3 on four platforms.
  • Figure 2: (a) Frequency of participant exposure to different types of abuse through social platforms. Many participants experienced abuse multiple times. (b) Distribution of abuse impact scores reported by survey respondents for specific instances of abuse they experienced. Respondents reported a total of 43 experienced abuse instances with a score of at least 4.
  • Figure 3: (a) Per-gender distribution of defense strategies adopted by survey respondents after exposure to abuse. Chi-square tests reveal a statistically significant correlation between gender and adopted defenses but not between adopted defenses and race or the impact of experienced abuse. (b) Per-gender preferences of social platform responses to abuse. Chi-squared tests show no statistically significant relationship between survey respondent suggestions and either gender, race, or impact of experienced abuse.