Quantifying Political Partisanship for Cross-Platform Analyses
2026-07-27T08:52:08Z•f554644083f29413276c8b35632de17f0c5505630a9407a95fa662092799aa95
AI safetyLLMsacademic researchalgorithmic biasconspiracy theoriescontent moderationdata ethicsgraph neural networksonline harmspolitical polarizationprivacyservice ecosystemssexual healthsocial networksurban segregation
What happened
This arXiv feed contains multidisciplinary studies on social networks, platform moderation, political polarization, conspiracy propagation, urban segregation, service ecosystems, graph neural networks, sexual-contact networks, and large language model behavior. The material is primarily academic and descriptive, with no disclosed software vulnerability, exploit, breach, or direct cybersecurity incident. Some findings have trust-and-safety relevance, particularly content moderation, conspiracy propagation, algorithmic bias, privacy, and societal harms from AI-mediated information systems.
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- f554644083f29413276c8b35632de17f0c5505630a9407a95fa662092799aa95
- Enrichment time
- 2026-07-27T08:52:08Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.