A Framework of Severity for Harmful Content Online
Morgan Klaus Scheuerman, Jialun Aaron Jiang, Casey Fiesler, Jed R. Brubaker
Abstract
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.
CCS Concepts: • Human-centered computing → Empirical studies in HCI; HCI theory, concepts and models.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 0b5a411a-855a-4b4c-a972-36315345df07Cited by top-tier papers36
- Human-AI Collaboration via Conditional Delegation: A Case Study of Content ModerationVivian Lai, Samuel Carton, Rajat Bhatnagar, Q. Vera Liao et al.CHI 2022 · 135 citations
- The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI RelationshipsRenwen Zhang, Han Li, Han Meng, Jinyuan Zhan et al.CHI 2025 · 122 citations
- SoK: A Framework for Unifying At-Risk User ResearchNoel Warford, Tara Matthews, Kaitlyn Yang, Omer Akgul et al.S&P 2022 · 101 citations
- Experiences of Harm, Healing, and Joy among Black Women and Femmes on Social MediaTyler Musgrave, Alia Cummings, Sarita SchoenebeckCHI 2022 · 82 citations
- Designing Word Filter Tools for Creator-led Comment ModerationShagun Jhaver, Quan Ze Chen, Detlef Knauss, Amy X. ZhangCHI 2022 · 70 citations
Builds on3
- Conformity of Eating Disorders through Content ModerationJessica L. Feuston, Alex S. Taylor, Anne Marie PiperCSCW 2020 · 82 citations
- "They Just Don't Get It": Towards Social Technologies for Coping with Interpersonal RacismAlexandra To, Wenxia Sweeney, Jessica Hammer, Geoff KaufmanCSCW 2020 · 64 citations
- Supporting Self-Injury Recovery: The Potential for Virtual Reality InterventionKaylee Payne Kruzan, Janis Whitlock, Natalya N. Bazarova, Katherine D. Miller et al.CHI 2020 · 14 citations
Related papers
- Toward a Feminist Social Media Vulnerability TaxonomyKristen Barta, Cassidy Pyle, Nazanin AndalibiCSCW 2023 · 9 citations
- With Visual Integrity and Care: A Framework for Mixed Methods Research on Visual Social DataNina Lutz, Joseph S. Schafer, Priya Dhawka, Phil Tinn et al.CHI 2026 · 2 citations
- "We Don't Want a Bird Cage, We Want Guardrails": Understanding & Designing for Preventing Interpersonal Harm in Social VR through the Lens of ConsentKelsea Schulenberg, Lingyuan Li, Caitlin Lancaster, Douglas Zytko et al.CSCW 2023 · 38 citations
- Women's Perspectives on Harm and Justice after Online HarassmentJane Im, Sarita Schoenebeck, Marilyn Iriarte, Gabriel Grill et al.CSCW 2022 · 61 citations
- Misinformation as a Harm: Structured Approaches for Fact-Checking PrioritizationConnie Moon Sehat, Ryan Li, Peipei Nie, Tarunima Prabhakar et al.CSCW 2024 · 22 citations
