Annotation of Positive vs Negative User Interactions for Social Sign Prediction
2026-06-05T08:52:20Z•a71801f3573c5221627b72de9ec24c145e23962d25cdfa1410e52d0365983b0d
citation-retrievalcultural-alignmentdeanonymizationemergent-coordinationgeodesic-searchgithubgovernancegroundinghallucinationllmmanipulationmastodonmisinformationmulti-agentnetwork-scienceontologypersonaprivacyqLORArecLMrecommender-systemsredditstanc e-simulationuser-profiling
What happened
Collection of recent arXiv CS (social/information) papers covering: zero-shot LLM annotation of interaction-level relational signals for sign prediction; RecLM, a unified framework that eliminates out-of-domain recommendations (includes Microsoft/RecAI GitHub link); reviews and methods for network model selection; RedditPersona, a modular Reddit-derived pipeline that trains QLoRA adapters per community (16M+ comments, user profiling); an audit framework showing LLM-based stance simulation is highly context-sensitive (risk of manipulated simulated stances); analysis of Mastodon governance at-s/
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- a71801f3573c5221627b72de9ec24c145e23962d25cdfa1410e52d0365983b0d
- Enrichment time
- 2026-06-05T08:52:20Z
- AI-assisted enrichment
- Yes
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