Leveraging Spatial Community Information in Location Recognition in Tweets
Article No.: 4, Pages 1 - 9
Abstract
Location names are very helpful in event extraction. Informal social texts pose significant challenges for recognizing location names. However, social texts have an advantage that can be leveraged: spatial and social network contexts. We address the location recognizing task as a part of named entity recognition, and introduce a new approach which leverages community contexts and captures language variations among groups of users. Specifically, we incorporate a community component into a topic modeling method and harness unlabeled tweets. Experiments on a large Twitter dataset show that our proposed method can improve the location classification F1 score by 5%.
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- Leveraging Spatial Community Information in Location Recognition in Tweets
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November 2017
50 pages
ISBN:9781450355001
DOI:10.1145/3148044
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Published: 07 November 2017
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SIGSPATIAL'17: 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 7, 2017
CA, Redondo Beach, USA
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