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Recently, many researchers have been focusing on the detection and classification of urban events by information analysis on social networks. Previous works mainly use text analysis of users' posts on social networks for detecting urban events. However, this approach has a limitation that the users' posts must mention the event for the analysis to be conducted. We propose a new method for classifying urban events by extracting user interest from the location-based social network information without text analysis. The proposed method includes analyzing common friends of users in the vicinity of the event venue and extracting common the friends' attributes by referring to related Wikipedia information. We designed and implemented the proposed method, and conducted an experiment for evaluating our method. Our experimental result shows that our method can classify events well in cases where participants have similar interests.
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Stored only when both papers are in the corpus — 4 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.