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| Natura: | Artículo científico |
| Lingua: | en |
| Pubblicazione: |
Instituto Politécnico Nacional
2016
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| Accesso online: | https://www.redalyc.org/articulo.oa?id=61547469010 |
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| _version_ | 1866815618468020224 |
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| author | Kwang-Yong Jeong |
| author_facet | Kwang-Yong Jeong |
| contents | Follower Behavior Analysis via Influential Transmitters on Social Issues in Twitter Kwang-Yong Jeong Kyung-Soon Lee Computación non supporting social issue Follower behavior supporting follower A follower can be divided into supporter, nonsupporter, or neutral according to a follower’s intention to a target user. Even though a follower is identified as a supporter, an opinion may not be positive to the target user. In this paper, we propose a method to classify a follower as supporter, non-supporter or neutral. To expand information of a follower, influential transmitters who support a target user are detected by using a modified HITS algorithm. To detect a follower’s specific opinion, social issues are extracted based on tweets of influential transmitters. The thread tweets are clustered based on Latent Dirichlet Allocation for social issues. Then, sentiment analysis is conducted for the clusters of a follower. To see the effectiveness of our method, a Korean tweet collection is constructed. As a result, we found that lots of supporting followers show opposite opinions depending on particular issues. 2016 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61547469010 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.20 |
| format | Artículo científico |
| id | redalyc_61547469010 |
| language | en |
| publishDate | 2016 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Follower Behavior Analysis via Influential Transmitters on Social Issues in Twitter Kwang-Yong Jeong Computación non supporting social issue Follower behavior supporting follower Follower Behavior Analysis via Influential Transmitters on Social Issues in Twitter Kwang-Yong Jeong Kyung-Soon Lee Computación non supporting social issue Follower behavior supporting follower A follower can be divided into supporter, nonsupporter, or neutral according to a follower’s intention to a target user. Even though a follower is identified as a supporter, an opinion may not be positive to the target user. In this paper, we propose a method to classify a follower as supporter, non-supporter or neutral. To expand information of a follower, influential transmitters who support a target user are detected by using a modified HITS algorithm. To detect a follower’s specific opinion, social issues are extracted based on tweets of influential transmitters. The thread tweets are clustered based on Latent Dirichlet Allocation for social issues. Then, sentiment analysis is conducted for the clusters of a follower. To see the effectiveness of our method, a Korean tweet collection is constructed. As a result, we found that lots of supporting followers show opposite opinions depending on particular issues. 2016 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61547469010 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.3 Vol.20 |
| title | Follower Behavior Analysis via Influential Transmitters on Social Issues in Twitter |
| topic | Computación non supporting social issue Follower behavior supporting follower |
| url | https://www.redalyc.org/articulo.oa?id=61547469010 |