Classifying Twitter Users for Spatio-temporal Entity Retrieval

• Item type: SIG Technical Reports(1)
• 公開日: 2012-12-05
• タイトル: Classifying Twitter Users for Spatio-temporal Entity Retrieval
• タイトル / 言語: en
• タイトル: Classifying Twitter Users for Spatio-temporal Entity Retrieval
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: ソーシャルコンピューティング
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Depatment of Social Informatics, Graduate School of Informatics, Kyoto University
• 著者所属: Depatment of Social Informatics, Graduate School of Informatics, Kyoto University
• 著者所属: Depatment of Social Informatics, Graduate School of Informatics, Kyoto University
• 著者所属(英): en
• 著者所属(英): Depatment of Social Informatics, Graduate School of Informatics, Kyoto University
• 著者所属(英): en
• 著者所属(英): Depatment of Social Informatics, Graduate School of Informatics, Kyoto University
• 著者所属(英): en
• 著者所属(英): Depatment of Social Informatics, Graduate School of Informatics, Kyoto University
• 著者名: Liang, Yan; Qiang, Ma; Masatoshi, Yoshikawa
• 著者名(英): Liang, Yan; Qiang, Ma; Masatoshi, Yoshikawa
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Spatio-temporal entity retrieval is a task for searching the entities with certain time and certain place, such as some commodities or events, from Twitter and Facebook, the social network with mass real-time update information. On Twitter, there are some users who tweet to the unspecified large number of other users, such as shops or local governments etc, while some other users who almost tweets to their friends. In this paper, we call the former as open account, while the latter as closed account. The expression in tweets and credibility of the two type of users can be different. For example, sometimes, an open account said "there are still some stock in the shop" about a commodity, while a closed account said "I didn't get it". In order to improve the accuracy of spatio-temporal ER, it is necessary to classify Twitter users. In this paper, we propose the method to classify Twitter users into open accounts and closed accounts. We use both the feature of user profile, such as address or telephone number etc. and the followers distribution. If the followers distribution is scattered, we treat it open account, while closed account otherwise.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Spatio-temporal entity retrieval is a task for searching the entities with certain time and certain place, such as some commodities or events, from Twitter and Facebook, the social network with mass real-time update information. On Twitter, there are some users who tweet to the unspecified large number of other users, such as shops or local governments etc, while some other users who almost tweets to their friends. In this paper, we call the former as open account, while the latter as closed account. The expression in tweets and credibility of the two type of users can be different. For example, sometimes, an open account said "there are still some stock in the shop" about a commodity, while a closed account said "I didn't get it". In order to improve the accuracy of spatio-temporal ER, it is necessary to classify Twitter users. In this paper, we propose the method to classify Twitter users into open accounts and closed accounts. We use both the feature of user profile, such as address or telephone number etc. and the followers distribution. If the followers distribution is scattered, we treat it open account, while closed account otherwise.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN10112482
• 書誌情報: 研究報告データベースシステム（DBS）; 巻 2012-DBS-156, 号 15, p. 1-6, 発行日 2012-12-05
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会