From Line Knowledge Digraphs to Sheaf Semantics: A Categorical Framework for Knowledge Graphs
2026-03-09T08:52:20Z•f4a8537bb80f9c4d00eac30b711d1a41ddb0b06866ec10919d659670cc6cc433
Digital-Services-ActSAGES-frameworkTikTokalgorithmic-auditcategorical-methodsconflict-forecastingcontent-moderationevent-forecastinggraph-neural-networkshuman-AI-collaborationinfluence-operationsinformation-operationsknowledge-graphslow-rank-banditsminors-profilingnarrative-manipulationpolarization-mitigationpolitical-violencesecurity-privacysheaf-semanticssocial-media-interventionstemporal-link-predictiontemporal-motifsundisclosed-advertisingvibe-coding
What happened
Collection of recent CS/social-science papers covering: (1) a categorical/sheaf-theoretic framework for knowledge graphs (theoretical foundations for contextual relational reasoning); (2) an actor-oriented SAGES framework for staged information campaigns and interventions (Seeding, Amplification, Galvanization, Expansion, Stickiness) with case studies of Myanmar and the Russia–Ukraine war; (3) an algorithmic audit of TikTok showing profile-driven delivery of influencer/undisclosed ads to accounts simulating minors and identifying a regulatory gap in the EU Digital Services Act; (4) methods for
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- f4a8537bb80f9c4d00eac30b711d1a41ddb0b06866ec10919d659670cc6cc433
- Enrichment time
- 2026-03-09T08:52:20Z
- AI-assisted enrichment
- Yes
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