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Discrete Dynamics in Nature and Society
Volume 2013 (2013), Article ID 903765, 8 pages
http://dx.doi.org/10.1155/2013/903765
Research Article

Two Applications of Clustering Techniques to Twitter: Community Detection and Issue Extraction

1Department of Computer Science and Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 139-701, Republic of Korea
2Tmaxsoft, Bundang-gu, Seongnam-si, Gyeonggi-do 463-824, Republic of Korea
3SK Telecom, Jung-gu, Seoul 100-999, Republic of Korea
4Future IT R&D Laboratory, LG Electronics Umyeon R&D Campus, 38 Baumoe-ro, Seocho-gu, Seoul 137-724, Republic of Korea

Received 25 July 2013; Revised 25 October 2013; Accepted 31 October 2013

Academic Editor: Daniele Fournier-Prunaret

Copyright © 2013 Yong-Hyuk Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Yong-Hyuk Kim, Sehoon Seo, Yong-Ho Ha, Seongwon Lim, and Yourim Yoon, “Two Applications of Clustering Techniques to Twitter: Community Detection and Issue Extraction,” Discrete Dynamics in Nature and Society, vol. 2013, Article ID 903765, 8 pages, 2013. doi:10.1155/2013/903765