HCAug 10, 2021

A Framework of Severity for Harmful Content Online

arXiv:2108.04401v2142 citations
AI Analysis

This provides a tool for researchers and policymakers to better prioritize and address various forms of online harm, though it is incremental as it builds on existing prioritization concepts.

The authors tackled the problem of prioritizing harmful content online by developing a theoretical framework of severity based on interviews and card-sorting with 52 participants, identifying four types of harm and eight dimensions to understand severity.

The proliferation of harmful content on online social media platforms has necessitated empirical understandings of experiences of harm online and the development of practices for harm mitigation. Both understandings of harm and approaches to mitigating that harm, often through content moderation, have implicitly embedded frameworks of prioritization - what forms of harm should be researched, how policy on harmful content should be implemented, and how harmful content should be moderated. To aid efforts of better understanding the variety of online harms, how they relate to one another, and how to prioritize harms relevant to research, policy, and practice, we present a theoretical framework of severity for harmful online content. By employing a grounded theory approach, we developed a framework of severity based on interviews and card-sorting activities conducted with 52 participants over the course of ten months. Through our analysis, we identified four Types of Harm (physical, emotional, relational, and financial) and eight Dimensions along which the severity of harm can be understood (perspectives, intent, agency, experience, scale, urgency, vulnerability, sphere). We describe how our framework can be applied to both research and policy settings towards deeper understandings of specific forms of harm (e.g., harassment) and prioritization frameworks when implementing policies encompassing many forms of harm.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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