• DocumentCode
    680823
  • Title

    Based on the Social Network Evaluation Model of Short-Term Interaction with Followers Micro-Blogging Marketing

  • Author

    Shuai Shao ; Cheng Li

  • Author_Institution
    Coll. of Autom., Huazhong Univ. of Sci. &Technol., Wuhan, China
  • fYear
    2013
  • fDate
    12-13 Dec. 2013
  • Firstpage
    8
  • Lastpage
    13
  • Abstract
    The paper presents an AISAS model used to describe the amplification, attenuation of influence and other complex process in marketing process, and the research of using influences and the amount of followers as an index in micro-blogging marketing. Specifically, we present a quantitative relationship between micro-blogging marketing influence and followers amounts used in information sharing, evaluation of marketing effects and adopting social network method to analysis users centrality from point centrality, between ness centrality and closeness centrality. Based on collecting, organizing true data of six typical marketing cases in Sina Micro-blogging, we use correlation and regression analysis to verify rationality of the model and give corresponding suggestions of developing marketing effect by using network topology relationships and searching key nodes.
  • Keywords
    marketing data processing; regression analysis; social networking (online); AISAS model; Sina Micro-blogging; closeness centrality; correlation analysis; followers microblogging marketing; information sharing; marketing process; network topology relationships; point centrality; regression analysis; searching key nodes; short-term interaction; social network evaluation model; social network method; Analytical models; Blogs; Companies; Data models; Mathematical model; Predictive models; Social network services; AISAS model; centrality; micro-blogging marketing; social network analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic and Social Media Adaptation and Personalization (SMAP), 2013 8th International Workshop on
  • Conference_Location
    Bayonne
  • Type

    conf

  • DOI
    10.1109/SMAP.2013.7
  • Filename
    6735560