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From smart cities to smart neighborhoods: detecting local events from social media

Li, Yang and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2014) From smart cities to smart neighborhoods: detecting local events from social media. In: Information Access in Smart Cities (i-ASC) 2014 Workshop in conjunction with ECIR 2014, 13 Apr 2014, Amsterdam, the Netherlands.

Abstract
There are several examples of work which uses data from so- cial media to detect events which occur in our real, physical world. Our target for event detection is to partition a large geographic region, a whole city in our case, into smaller districts based on geotagged Tweets and to detect smaller local events. We generate a language model for Tweets from each district and measure the KL divergence on incoming Tweets to detect outliers. When these reach a sizable volume or intensity and are consistent, this indicates an event within that district. We used Tweets drawn from Dublin city and we describe experiments on partitioning the city into districts and detecting local events within districts.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:Smart cities; Event detection; Twitter
Subjects:Computer Science > Multimedia systems
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:http://dcs.gla.ac.uk/workshops/iASC2014/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, IBM
ID Code:19919
Deposited On:25 Apr 2014 14:47 by Alan Smeaton . Last Modified 31 Oct 2018 11:57
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