• DocumentCode
    3051813
  • Title

    Users´ classification and usage-pattern identification in academic social networks

  • Author

    Almousa, Omar

  • Author_Institution
    Inf. Technol. Dept., AlBalqa Appl. Univ., Assalt, Jordan
  • fYear
    2011
  • fDate
    6-8 Dec. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Academic social networking sites are becoming increasingly popular. Several groups of academic people at different level of their career and from different disciplines are utilizing them for their benefit. This paper aims to explore usage patterns of an academic Social Networking Site (SNS) (namely Academia.edu) by different groups of academic users. It gains its importance because of the lack of academic social networking sites studies especially those concerning different user types and usage patterns of academic social networking sites.
  • Keywords
    educational administrative data processing; pattern classification; social networking (online); Academia.edu; academic social networking sites; usage-pattern identification; user classification; user types; Art; Chemistry; Computer science; Engineering profession; Materials; Medical services; Social network services; Collaborative software; Facebook; Human computer interaction; LinkedIn; Social Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Electrical Engineering and Computing Technologies (AEECT), 2011 IEEE Jordan Conference on
  • Conference_Location
    Amman
  • Print_ISBN
    978-1-4577-1083-4
  • Type

    conf

  • DOI
    10.1109/AEECT.2011.6132525
  • Filename
    6132525