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2011 IEEE Fifth International Conference on Semantic Computing
Understanding Cancer-Based Networks in Twitter Using Social Network Analysis
Palo Alto, California USA
September 18-September 21
ISBN: 978-0-7695-4492-2
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.
Index Terms:
social network analysis, virtual social networks, cancer-based Twitter networks, data visualization, trust inference, information-flow
Citation:
Dhiraj Murthy, Alexander Gross, Daniela Oliveira, "Understanding Cancer-Based Networks in Twitter Using Social Network Analysis," icsc, pp.559-566, 2011 IEEE Fifth International Conference on Semantic Computing, 2011
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