Presenting novel application-based centrality measures for finding important users based on their activities and social behavior.
There are more important relationships based on users' behavior and the done activities than those of friendship in online social networks. Study of social behavior of users in these networks has many applications. Analyzing online social networks' activity graphs, as a better representation of user...
| Publicado en: | Computers in Human Behavior Vol. 73; pp. 64 - 80 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Elsevier B.V.
Aug2017
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=123258435&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 123258435 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: Aug2017 vid: 73 pid: 2410 pub: Elsevier B.V. artinfo: ui: 123258435 10.1016/j.chb.2017.03.014 ppf: 64 ppct: 16 formats: tig: atl: Presenting novel application-based centrality measures for finding important users based on their activities and social behavior. aug: au: Khadangi, Ehsan Bagheri, Alireza affil: Computer Engineering and Information Technology Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Hafez Ave, 424, Iran su: Social networks World Wide Web Social media Behavioral assessment Application software sug: subj: Social networks World Wide Web Social media Software Publishers Software publishers (except video game publishers) Custom Computer Programming Services Other Individual and Family Services Internet Publishing and Broadcasting and Web Search Portals Behavioral assessment Application software keyword: Activity network Centrality measure Social behavior Social media marketing Social network analysis Activity network Centrality measure Social behavior Social media marketing Social network analysis ab: There are more important relationships based on users' behavior and the done activities than those of friendship in online social networks. Study of social behavior of users in these networks has many applications. Analyzing online social networks' activity graphs, as a better representation of users' social behavior, may open new perspectives for real applications such as finding important users. Although detecting these influential nodes based on their friendship relationships is studied a lot, finding important nodes using users' behavior and activates has not attracted much attention. In this work, we study users' importance in various Facebook activity networks including like, comment, post, share, and mixed, then compare gained rankings with those of the friendship network and conclude that users influence analysis in activity networks represents very different results. Afterwards, we propose new centrality measures that can present different rankings suitable for different applications, further to have the potential for simultaneous consideration of various activities in a multilayer network. Experimental results highlights the benefits of using the presented methods. To the best of our knowledge, our methods are the first and only proposed centrality measures that can present different rankings for various applications based on users' social behavior. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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