一般ユーザの観点に基づくTwitterからの人物関係の可視化と事例の考察  [in Japanese] Visualization of the Human Relationships from Twitter Based on the Mass Audience and Consideration of Its Case Studies  [in Japanese]

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Abstract

マイクロブログサービスの1つであるTwitterでは,その時々で話題になる政治家や芸能人など有名人に関する一般ユーザの発言を豊富に得ることができる.さらに近年では,SNSから得られる評判情報をマーケティングやその他のサービスに応用しようという試みが活発に行われている.そこで本研究では,Twitterから得られる評判情報のうち,一般ユーザの有名人に関する発言とその発言を行ったユーザのプロフィールなどに着目する.これらの各情報源から得られるデータに対し,抽出の妨げとなるノイズへの前処理を経て,一般ユーザの観点が反映された特徴量であるトピックの抽出を行う.そして得られたトピックの比率をもとに人物の類似関係を獲得し,それをもとに各人物を平面上に配置することで,人物関係の可視化を行う.この可視化結果に対して,使用した情報源ごと,および可視化手法ごとに,妥当性と発見性に着目した特徴の分析を行う.Recently, it is popular to exploit users' comments or reviews in SNS for marketing research. Twitter, which is one of micro blog services, is one of the popular information sources used for the above purpose. We especially try to extract the information according to celebrities like politicians, actors, comedians, singers and so on. This will be useful for understanding the celebrities. In our study, we use ordinary people's tweet according to a celebrity and the user profile of the tweet's author. We develop a system that visualizes the relationship of celebrities from the viewpoint of ordinary people. For this purpose, we delete some noise text from the tweets, extract latent topics that present the celebrities' characteristics and allocate them on two dimensional plane based on the similarities of topics. We examine the visualization results from the viewpoint of validity and discovery.

Recently, it is popular to exploit users' comments or reviews in SNS for marketing research. Twitter, which is one of micro blog services, is one of the popular information sources used for the above purpose. We especially try to extract the information according to celebrities like politicians, actors, comedians, singers and so on. This will be useful for understanding the celebrities. In our study, we use ordinary people's tweet according to a celebrity and the user profile of the tweet's author. We develop a system that visualizes the relationship of celebrities from the viewpoint of ordinary people. For this purpose, we delete some noise text from the tweets, extract latent topics that present the celebrities' characteristics and allocate them on two dimensional plane based on the similarities of topics. We examine the visualization results from the viewpoint of validity and discovery.

Journal

  • IPSJ Journal

    IPSJ Journal 56(3), 972-982, 2015-03-15

    Information Processing Society of Japan (IPSJ)

Codes

  • NII Article ID (NAID)
    110009884091
  • NII NACSIS-CAT ID (NCID)
    AN00116647
  • Text Lang
    JPN
  • Article Type
    Journal Article
  • ISSN
    1882-7764
  • Data Source
    NII-ELS  IPSJ 
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