• DocumentCode
    630119
  • Title

    TALISON - Tensor analysis of social media data

  • Author

    Kao, Anne ; Ferng, William ; Poteet, Steve ; Quach, Lesley ; Tjoelker, Robert

  • Author_Institution
    Boeing Res. & Technol., Seattle, WA, USA
  • fYear
    2013
  • fDate
    4-7 June 2013
  • Firstpage
    137
  • Lastpage
    142
  • Abstract
    With the growth in social media, online forums have become major sources of data for social network analysis and a major research area in data analytics. However, many aspects of social networks have not been addressed fully, if at all. First, there is the need to capture various parts of the content of the exchanges, for example, bare text and hashtags, which constitute some of the major features of social media networks. Second, as in all social networks, there are many different types of relationships; for example, “following” and “friend” relationships, as well as relationships defined in terms of how users interact with one another such as replying, quoting, retweeting, and mentioning. Finally, an important aspect of analysis of social networks is temporal dynamics and topic evolution. We offer an analysis of Twitter data using tensors which can incorporate all of these different aspects in a single representation and both identify salient events and distinguish important views of these events.
  • Keywords
    data analysis; social networking (online); tensors; TALISON; Twitter data analysis; data analytics; online forums; social media data; social media networks; social network analysis; social network relationship types; temporal dynamics; tensor analysis of latent interactions in social online networks; topic evolution; Analytical models; Internet; Media; Tensile stress; Twitter; Vectors; social media; social network analysis; tensor analysis; text analytics; text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence and Security Informatics (ISI), 2013 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    978-1-4673-6214-6
  • Type

    conf

  • DOI
    10.1109/ISI.2013.6578803
  • Filename
    6578803