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Tweet-SCAN: an event discovery technique for geo-located tweets

Author
Capdevila, J.; Cerquides, J.; Nin, J.; Torres, J.
Type of activity
Journal article
Journal
Pattern recognition letters
Date of publication
2017-07-01
Volume
93
First page
58
Last page
68
DOI
https://doi.org/10.1016/j.patrec.2016.08.010 Open in new window
Repository
http://hdl.handle.net/2117/106626 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0167865516302124 Open in new window
Abstract
Twitter has become one of the most popular Location-based Social Networks (LBSNs) that bridges physical and virtual worlds. Tweets, 140-character-long messages, are aimed to give answer to the What’s happening? question. Occurrences and events in the real life (such as political protests, music concerts, natural disasters or terrorist acts) are usually reported through geo-located tweets by users on site. Uncovering event-related tweets from the rest is a challenging problem that necessarily r...
Citation
Capdevila, J., Cerquides, J., Nin, J., Torres, J. Tweet-SCAN: an event discovery technique for geo-located tweets. "Pattern recognition letters", 1 Juliol 2017, vol. 93, p. 58-68.
Keywords
DBSCAN, Event discovery, Hierarchical Dirichlet Process (HDP), Probabilistic topic models, Twitter, Unsupervised learning
Group of research
CAP - High Performace Computing Group

Participants

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