Towards the downstream effects of insufficient content moderation on the internet
Ruffin, Margie
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https://hdl.handle.net/2142/129430
Description
Title
Towards the downstream effects of insufficient content moderation on the internet
Author(s)
Ruffin, Margie
Issue Date
2025-04-23
Director of Research (if dissertation) or Advisor (if thesis)
Wang, Gang
Doctoral Committee Chair(s)
Wang, Gang
Levchenko, Kirill
Committee Member(s)
Cobb, Camille
Xiong, Aiping
Department of Study
Siebel School Comp & Data Sci
Discipline
Computer Science
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Content Moderation
AI-generated media (images
videos
text)
Copyright Violations
Academic Integrity Violations
Language
eng
Abstract
Internet platforms rely heavily on content moderation to help drive positive engagement. Historically, this task has been done by humans, but in the recent decade, ML/AI models have been developed to reduce the burden by filtering out abusive content. While a step in the right direction, some moderation practices, manual and automated (e.g., context labeling, deepfake detection, and self-moderation), can still inadvertently cause harm to individual Internet users. To prevent the perpetuation of these harms, we must understand how they manifest regarding individuals’ perceptions, sentiments, and behaviors. This dissertation investigates how the ineffective content moderation practices of internet platforms affect how individuals respond to online abuse. Specifically, this dissertation explores how explanations (content-labeling) impact their viewers’ perceptions and sentiments (Chapter 3), how unmonitored deepfake-enabled profiles can sway an individual’s perception of and engagement with fake news (Chapter 4), and how low-moderation of platforms results in self-moderation to combat copyright violation harms (Chapter 5). In summary, these works show the downstream effects of deceitful and unauthorized content that slips through the moderation cracks, and assessing them is essential for developing better interventions.
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