Algorithmic Cultivation: How Social Media Feeds Shape User Language

2026-05-19T08:52:16Zd398a14c6868596926aa43a21dab9bdcd497e5d0ec6d585b960fe166e0f62ff7
CERT-datasetsDSAacademic-integrityalgorithmic-influenceanomaly-detectionbehavioral-analyticsdata-qualitydatasetsepidemic-modellinggenerative-AIhypergraphinsider-threatlanguage-changereproducibilityresearch-metricssocial-mediatransparency

What happened

Collection of recent arXiv papers (May 19, 2026) with multiple security-relevant items. Notable works: MV-Gate — a new multi-view insider-threat detection framework that fuses statistical recurrence/frequency signals with tokenized activity sequences using an anomaly-aware gating mechanism; demonstrates improved detection on CERT r4.2/r5.2 and ADFA-LD, especially for low-signal progressive insiders. A study of algorithmic feed effects on language (Bluesky) shows sustained feed exposure causes measurable stylistic and psycholinguistic shifts, with implications for platform manipulation and user

Why it matters

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

Evidence and limitations

Source ID
arxiv_cs_si
Record identifier
d398a14c6868596926aa43a21dab9bdcd497e5d0ec6d585b960fe166e0f62ff7
Enrichment time
2026-05-19T08:52:16Z
AI-assisted enrichment
Yes

This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.

Record · Algorithmic Cultivation: How Social Media Feeds Shape User Language · Baitaphish