AI RESEARCH
Causal Reconstruction of Sentiment Signals from Sparse News Data
arXiv CS.LG
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ArXi:2603.23568v1 Announce Type: new Sentiment signals derived from sparse news are commonly used in financial analysis and technology monitoring, yet transforming raw article-level observations into reliable temporal series remains a largely unsolved engineering problem.