Majority Correctness in Social Networks: From Well-Mixed Electorates to Complex Networks
2026-07-17T08:52:12Z•3dde90b22835de08656f5a3a4882d2197022d8f9fa59d1c3e3af0194cb1aa205
LLM-agentsalgorithmic-robustnesscommunity-detectioncoordinated-influencedisinformationgraph-algorithmsinfluence-operationsmeasurement-errorplatform-manipulationprediction-marketsrecommender-systemssocial-networks
What happened
Collection of recent research (arXiv 2026) covering networked social processes, measurement, and algorithmic vulnerabilities relevant to information security and platform integrity. Key contributions: a theoretical and empirical study of majority correctness under social influence and zealots (shows social updating can degrade aggregate accuracy and identifies topology-dependent tipping points); an empirical analysis of Kalshi sports prediction-market prices revealing time-to-expiry and product-type calibration biases; a forensic reclassification of state-backed influence campaigns that disent
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- 3dde90b22835de08656f5a3a4882d2197022d8f9fa59d1c3e3af0194cb1aa205
- Enrichment time
- 2026-07-17T08:52:12Z
- AI-assisted enrichment
- Yes
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