A Guide to Using Social Media as a Geospatial Lens for Studying Public Opinion and Behavior

2026-04-10T08:52:43Z7ade383d11d725276a8a6f6eb077b18e1962f8a58df5e8d09dad75a7907b5c8a
LLM-safetyalgorithmsautonomy-safetyconfidence-intervalsconformal-predictiongeospatial-analyticshuman-in-the-loophypergraph-analysismeasurementmodel-adoption-metricsmulti-agent-debatenetwork-security-metricsnetwork-segmentationsamplingsocial-media-intelligencestatistical-estimatorzero-trust

What happened

This silver document aggregates five recent arXiv papers. Key security-relevant contributions: (1) “How segmented is my network?” defines a statistically principled scalar metric (segmentedness = fraction of disallowed node-pair communications) for measuring network segmentation, derives a normalized estimator with confidence intervals, and shows that M=97 uniformly sampled node-pairs suffices for a 95% CI with ±0.1 margin; applications include baseline tracking, zero-trust assessment, and merger integration. (2) “From Debate to Decision: Conformal Social Choice” proposes a post-hoc conformal‑

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_si
Record identifier
7ade383d11d725276a8a6f6eb077b18e1962f8a58df5e8d09dad75a7907b5c8a
Enrichment time
2026-04-10T08:52:43Z
AI-assisted enrichment
Yes

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