• DocumentCode
    623837
  • Title

    Enterprise social network analysis and modeling: A tale of two graphs

  • Author

    Jin Cao ; Hongyu Gao ; Li, Li Erran ; Friedman, Bruce

  • Author_Institution
    Bell Labs., Alcatel-Lucent, Holmdel, NJ, USA
  • fYear
    2013
  • fDate
    14-19 April 2013
  • Firstpage
    2382
  • Lastpage
    2390
  • Abstract
    Like their public counterpart such as Facebook and Twitter, enterprise social networks are poised to revolutionize how people interact in the workplace. There is a pressing need to understand how people are using these social networks. Unlike the public social networks like Facebook or Twitter which are normally characterized using the social graph or the interaction graph, enterprise social networks are also governed by an organization graph. Based on a six month dataset collected from May through October 2011 of a large enterprise social network, we study the characteristics of activities of its enterprise social network. We observe that the user attributes in the organization graph such as geographic location (eg. country) and his/her rank in the company hierarchy have a significant impact on how the user uses the social network and how user interacts with each other. We then build formal statistical models of user interaction graphs in enterprise social network and quantify effects of user attributes from organization graphs on these interactions. Furthermore, as the enterprise social network medium bring users from diverse locations and social status forming ad-hoc communities, our statistical model can be further enhanced by including these ad-hoc communities.
  • Keywords
    graph theory; social networking (online); statistical analysis; Facebook; Twitter; enterprise social network analysis; formal statistical model; geographic location; organization graph; public social network; social graph; user interaction graph; Blogs; Communities; Companies; Logistics; Twitter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2013 Proceedings IEEE
  • Conference_Location
    Turin
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4673-5944-3
  • Type

    conf

  • DOI
    10.1109/INFCOM.2013.6567043
  • Filename
    6567043