DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Gwan | ko |
dc.contributor.author | Myaeng, Sung-Hyon | ko |
dc.date.accessioned | 2020-02-12T01:20:26Z | - |
dc.date.available | 2020-02-12T01:20:26Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2015-08 | - |
dc.identifier.citation | IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, pp.573 - 578 | - |
dc.identifier.uri | http://hdl.handle.net/10203/272285 | - |
dc.description.abstract | 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. | - |
dc.language | English | - |
dc.publisher | Association for Computing Machinery, Inc | - |
dc.title | Analysis of spatially oriented topic versatility over time on social media | - |
dc.type | Conference | - |
dc.identifier.wosid | 000371793500083 | - |
dc.identifier.scopusid | 2-s2.0-84962592245 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 573 | - |
dc.citation.endingpage | 578 | - |
dc.citation.publicationname | IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 | - |
dc.identifier.conferencecountry | FR | - |
dc.identifier.conferencelocation | Paris | - |
dc.identifier.doi | 10.1145/2808797.2809378 | - |
dc.contributor.localauthor | Myaeng, Sung-Hyon | - |
dc.contributor.nonIdAuthor | Jang, Gwan | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.