著者

David Ramamonjisoa

出版者

一般社団法人情報処理学会

雑誌

情報処理学会研究報告. 情報学基礎研究会報告

巻号頁・発行日

vol.2014, no.3, pp.1-6, 2014-01-31

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User-contributed comments are one of the hallmarks of the Social Web, widely adopted across social media sites and mainstream news providers alike. While comments encourage higher-levels of user engagement with online media, their wide success places new burdens on users to process and assimilate the perspectives of number of user-contributed perspectives. This paper describes a comparison between two methods for analyzing topic trends from users' comments in social media. The first method is using the information retrieval weight tfidf and empirical topic extraction algorithm. The second one is based on the topic modeling.