Relationship between SNS users' posting activities and their interests

• Item type: SIG Technical Reports(1)
• 公開日: 2017-12-15
• タイトル: Relationship between SNS users' posting activities and their interests
• タイトル / 言語: en
• タイトル: Relationship between SNS users' posting activities and their interests
• 言語: eng
• 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: Graduate School of Information, Production and Systems, Waseda University
• 著者所属: Graduate School of Information, Production and Systems, Waseda University
• 著者所属: Graduate School of Information, Production and Systems, Waseda University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information, Production and Systems, Waseda University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information, Production and Systems, Waseda University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information, Production and Systems, Waseda University
• 著者名: Bin, Du; Wenbo, Su; Mizuho, Iwaihara
• 著者名(英): Bin, Du; Wenbo, Su; Mizuho, Iwaihara
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Users from the entire world interact with others, share feelings and do various activities on SNSs. Such activities of users potentially have strong relationships with their interests and preferences. In this paper, we investigate relationship between public posting activities, online behaviors of users and their belonging interest groups, to identify representative user types, and compare distribution of these user types in each interest group. Public posts of users in several Facebook interest groups have been collected, and linguistic features such as the length of each post have been extracted. The polarity and the subjectivity of posts have been obtained through sentiment analysis. Combined with activity features of these users, post-level clustering and user-level clustering are carried out by several clustering algorithms, and six user types representing these clusters are identified. We observe that distribution of these user types is distinctively different between interest groups, and this fact is useful for predicting users' interests.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Users from the entire world interact with others, share feelings and do various activities on SNSs. Such activities of users potentially have strong relationships with their interests and preferences. In this paper, we investigate relationship between public posting activities, online behaviors of users and their belonging interest groups, to identify representative user types, and compare distribution of these user types in each interest group. Public posts of users in several Facebook interest groups have been collected, and linguistic features such as the length of each post have been extracted. The polarity and the subjectivity of posts have been obtained through sentiment analysis. Combined with activity features of these users, post-level clustering and user-level clustering are carried out by several clustering algorithms, and six user types representing these clusters are identified. We observe that distribution of these user types is distinctively different between interest groups, and this fact is useful for predicting users' interests.
• 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 2017-DBS-166, 号 14, p. 1-6, 発行日 2017-12-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-871X
• 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