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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
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The effectiveness of moderating harmful online content.

Philipp J Schneider1, Marian-Andrei Rizoiu2

  • 1College of Management of Technology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.

Proceedings of the National Academy of Sciences of the United States of America
|August 14, 2023
PubMed
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The EU Digital Services Act (DSA) can effectively reduce online harm. This study shows that even with fast platforms like Twitter, timely content moderation significantly mitigates risks from viral harmful material.

Keywords:
content moderationharm reductionharmful contentstochastic modeling

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Area of Science:

  • Online content moderation
  • Digital policy
  • Computational social science

Background:

  • The EU Digital Services Act (DSA) mandates platforms to moderate harmful online content.
  • Trusted flaggers identify content, requiring platform removal within a set timeframe (e.g., 24 hours).
  • Highly viral content with short lifespans presents unique moderation challenges.

Purpose of the Study:

  • To analyze the effectiveness of EU-mandated content moderation delays.
  • To quantify harm reduction achieved by regulating viral online content.
  • To develop a method for estimating moderation effectiveness and optimizing flagger workload.

Main Methods:

  • Utilized self-exciting point processes to model viral content dynamics.
  • Simulated the impact of varying moderation delays on harm reduction.
  • Developed a framework for platform-specific moderation effectiveness estimation.

Main Results:

  • Harm reduction is achievable, particularly for the most damaging content.
  • Effectiveness is demonstrated even on high-speed platforms like Twitter.
  • The proposed method provides a data-driven approach to content flagging and workload management.

Conclusions:

  • The DSA's moderation framework can be effective in mitigating online harm.
  • Optimizing moderation delays is crucial for managing viral content risks.
  • The developed methodology aids in efficient content moderation and resource allocation.