1. Twitter user geolocation by filtering of highly mentioned users.
- Author
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Ebrahimi, Mohammad, ShafieiBavani, Elaheh, Wong, Raymond, and Chen, Fang
- Subjects
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GEOGRAPHIC information systems , *CELEBRITIES , *POPULATION geography , *SOCIAL networks , *TEXT messages , *SOCIAL media - Abstract
Geolocated social media data provide a powerful source of information about places and regional human behavior. Because only a small amount of social media data have been geolocation‐annotated, inference techniques play a substantial role to increase the volume of annotated data. Conventional research in this area has been based on the text content of posts from a given user or the social network of the user, with some recent crossovers between the text‐ and network‐based approaches. This paper proposes a novel approach to categorize highly‐mentioned users (celebrities) into Local and Global types, and consequently use Local celebrities as location indicators. A label propagation algorithm is then used over the refined social network for geolocation inference. Finally, we propose a hybrid approach by merging a text‐based method as a back‐off strategy into our network‐based approach. Empirical experiments over three standard Twitter benchmark data sets demonstrate that our approach outperforms state‐of‐the‐art user geolocation methods. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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