Algorithmic Cultivation: How Social Media Feeds Shape User Language
2026-05-19T08:52:16Z•d398a14c6868596926aa43a21dab9bdcd497e5d0ec6d585b960fe166e0f62ff7
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.