Analysis of spatially oriented topic versatility over time on social media

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People in different regions or times may have different views and therefore may talk about different sub-topics in a social media. Versatility of a topic in this research refers to the degree to which a topic discussed in a social media covers different points of view or sub-topics. We introduce this notion of versatility for individual topics embedded in Twitter data originated from different regions over time. Uniqueness of a region with respect to a topic is first computed based on how its term distribution differs from those in other regions. Uniqueness values associated with all the regions for a topic are then used to compute its versatility. Since versatility of a topic captures its characteristics across different regions, identifying versatile topics can help understanding regional interests and thus providing region-dependent services. In addition, it becomes possible to identify regions with minority sub-topics, which can be buried easily. By analyzing topic versatility over time, furthermore, we can analyze the behavior of a topic in terms of when it is diverged or converged across the regions.
Publisher
Association for Computing Machinery, Inc
Issue Date
2015-08
Language
English
Citation

IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, pp.573 - 578

DOI
10.1145/2808797.2809378
URI
http://hdl.handle.net/10203/272285
Appears in Collection
CS-Conference Papers(학술회의논문)
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