Identifying social roles using heterogeneous features in online social networks.
Role analysis plays an important role when exploring social media and knowledge‐sharing platforms for designing marking strategies. However, current methods in role analysis have overlooked content generated by users (e.g., posts) in social media and hence focus more on user behavior analysis. The u...
| Publicado en: | Journal of the Association for Information Science & Technology Vol. 70; no. 7; pp. 660 - 675 |
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| Autores principales: | , , , , , |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jul2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136821898&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136821898 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23301635 H6JN jtl: Journal of the Association for Information Science & Technology issn: 23301635 maglogo: N pubinfo: dt: Jul2019 vid: 70 iid: 7 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 136821898 136821898 136821898 10.1002/asi.24160 136821898 ppf: 660 ppct: 15 formats: tig: atl: Identifying social roles using heterogeneous features in online social networks. aug: au: Liu, Yezheng Du, Fei Sun, Jianshan Silva, Thushari Jiang, Yuanchun Zhu, Tingting affil: School of management, Hefei University of Technology, Hefei, 230009 China sug: subj: Community Role Social Networks Utilization User-Computer Interface Models, Theoretical Internet Access Conceptual Framework Random Sample Multivariate Analysis Probability Human Funding Source ab: Role analysis plays an important role when exploring social media and knowledge‐sharing platforms for designing marking strategies. However, current methods in role analysis have overlooked content generated by users (e.g., posts) in social media and hence focus more on user behavior analysis. The user‐generated content is very important for characterizing users. In this paper, we propose a novel method which integrates both user behavior and posted content by users to identify roles in online social networks. The proposed method models a role as a joint distribution of Gaussian distribution and multinomial distribution, which represent user behavioral feature and content feature respectively. The proposed method can be used to determine the number of roles concerned automatically. The experimental results show that the proposed method can be used to identify various roles more effectively and to get more insights on such characteristics. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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