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    題名: Discovering political tendency in bulletin board discussions by social community analysis
    作者: Lee, K.-C.;Shan, Mankwan
    沈錳坤
    貢獻者: 資科系
    關鍵詞: Bulletin board systems;Discussion boards;Graph clustering;Graph colorings;Graph partition;Linguistic analysis;Social communities;Social interactions;Social Networks;Clustering algorithms;Information management;Bulletin boards
    日期: 2009-12
    上傳時間: 2015-05-07 15:28:24 (UTC+8)
    摘要: Bulletin Board System (BBS) is very popular and provide an asynchronous, text-based environment for users to exchange information and idea. A BBS consists of a number of discussion boards, each of which focuses on a particular subject. A discussion on a topic consists of a seed articles followed by some articles responsive to the seed article or other responsive articles. This paper investigates the social community analysis technique to discover the political tendency of users within the boards from discussions. We first extract the social interactions between users, such as "reply" and "advocate" ofposts between users. A social network among users is constructed based on the extracted social interaction. After building the social network, we employ the graph partition, graph coloring, and graph clustering algorithms respectively to discover the social communities. Users of the same community have more potential of political opinion agreement with each other. By using this approach, we are able to partition users into two opposite groups and identify their political tendency effectively without linguistic analysis of discussion content. © 2009 IEEE.
    關聯: 4th International Conference on Digital Information Management, ICDIM 2009,1-5
    資料類型: conference
    DOI 連結: http://dx.doi.org/10.1109/ICDIM.2009.5356800
    DOI: 10.1109/ICDIM.2009.5356800
    顯示於類別:[資訊科學系] 會議論文

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