Consensus drift analysis for training language models to follow instructions with human feedback. How sentiment and opinion have shifted over time, with inflection points and trigger events identified.
Results synthesized from web crawls, academic citations (Semantic Scholar), patent filings (USPTO), corporate ownership records (SEC EDGAR, Companies House), software dependency graphs (npm, PyPI, crates.io), infrastructure records (DNS, TLS certificates, IP ranges), temporal archives (Wayback Machine), government datasets (Data.gov), and conversational sources (Hacker News, Reddit).