2019
DOI: 10.3390/electronics8060692
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Urban Crowd Detection Using SOM, DBSCAN and LBSN Data Entropy: A Twitter Experiment in New York and Madrid

Abstract: The surfer and the physical location are two important concepts associated with each other in the social network-based localization service. This work consists of studying urban behavior based on location-based social networks (LBSN) data; we focus especially on the detection of abnormal events. The proposed crowd detection system uses the geolocated social network provided by the Twitterapplication programming interface (API) to automatically detect the abnormal events. The methodology we propose consists of … Show more

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References 38 publications
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