• DocumentCode
    2058496
  • Title

    Understanding Cancer-Based Networks in Twitter Using Social Network Analysis

  • Author

    Murthy, Dhiraj ; Gross, Alexander ; Oliveira, Daniela

  • Author_Institution
    Sociology Dept., Bowdoin Coll., Brunswick, ME, USA
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    559
  • Lastpage
    566
  • Abstract
    Web-based social media networks have an increasing frequency of health-related information, resources, and networks (both support and professional). Although we are aware of the presence of these health networks, we do not yet know their ability to (1) influence the flow of health-related behaviors, attitudes, and information and (2) what resources have the most influence in shaping particular health outcomes. Lastly, the health research community lacks easy-to-use data gathering tools to conduct applied research using data from social media websites. In this position paper we discuss and sketch our current work on addressing fundamental questions about information flow in cancer-related social media networks by visualizing and understanding authority, trust, and cohesion. We discuss the development of methods to visualize these networks and information flow on them using real-time data from the social media website Twitter and how these networks influence health outcomes by examining responses to specific health messages.
  • Keywords
    cancer; health care; social networking (online); Twitter; Web-based social media networks; cancer-based networks; health-related information; social media Websites; social network analysis; Cancer; Data visualization; Media; Peer to peer computing; Twitter; cancer-based Twitter networks; data visualization; information-flow; social network analysis; trust inference; virtual social networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2011 Fifth IEEE International Conference on
  • Conference_Location
    Palo Alto, CA
  • Print_ISBN
    978-1-4577-1648-5
  • Electronic_ISBN
    978-0-7695-4492-2
  • Type

    conf

  • DOI
    10.1109/ICSC.2011.51
  • Filename
    6061372