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Guided Clustering for Social Media Nowcasting

Summary: Guided, interactive clustering of massive social-media feature spaces (billions of features) to enable nowcasting for low-/no-training-data phenomena by surfacing interpretable clusters under multiple relatedness metrics (statistical, semantic). Supports rapid user feedback (merge/split) and optimization to avoid full re-clustering, trading conventional clustering metrics for conformity with domain priors so users can iteratively produce usable features without supervised labels. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
241
Venue
CIDR
Year
2015
Pagerank
-
Overall Rank
13,366 | 7.02%
DOI
-

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