Cross Event Detection and Topic Evolution Mining in cross events for Man Made Disasters in Social Media Streams
2026-04-06T08:52:17Z•9de652491eef5d4130ce5bd664b4b609420d2adc5d1dc7fb89a8a7d09985ad49
AutoVerifierCEEDKatz centralityLLM agentsPRISMS&TIad-tech supply chainautomated verificationchatbots in educationdark poolingevent detectionlarge language modelsmisinformationmulti-stakeholder disclosurenetwork formationscientific & technical intelligencesemantic clusteringsimulationssocial media monitoringsynthetic contenttopic evolutionvulnerability managementvulnerability notification
What happened
Collection of recent CS/SI arXiv papers focused on social-media analytics, LLM-enabled tools, and ad-tech supply-chain vulnerabilities. Key contributions include: CEED, a cross-event detection and topic-evolution framework for disaster-related social streams; PRISM, an LLM-guided semantic clustering method for high-precision topic discovery; AutoVerifier, an agentic LLM-based pipeline for end-to-end technical-claim verification; evaluations of custom vs general-purpose GAI chatbots in science education; LLM-agent social-network simulations; a network-formation game using Katz centrality; and a
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- 9de652491eef5d4130ce5bd664b4b609420d2adc5d1dc7fb89a8a7d09985ad49
- Enrichment time
- 2026-04-06T08:52:17Z
- AI-assisted enrichment
- Yes
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