are those that are open and accessible to anyone. Conversations can occur between many individuals behind closed walls, e.g., a major company’s employees working on a major project.
Published in Chapter:
Finding Meaning in Online, Very-Large Scale Conversations
Brian K. Smith (Pennsylvania State University, USA), Priya Sharma (Pennsylvania State University, USA), Kyu Yon Lim (Pennsylvania State University, USA), Goknur Kaplan Akilli (Pennsylvania State University, USA), KyoungNa Kim (Pennsylvania State University, USA), and Toru Fujimoto (Pennsylvania State University, USA)
Copyright: © 2009
|Pages: 21
DOI: 10.4018/978-1-59904-974-8.ch015
Abstract
Computers and networking technologies have led to increases in the development and sustenance of online communities, and much research has focused on examining the formation of and interactions within these virtual communities. The methods for collecting data and analyzing virtual online communities, especially very large-scale online discussion forums can be varied and complex. In this chapter, we describe two analytical methods—qualitative data analysis and Social Network Analysis (SNA)–that we used to examine conversations within ESPN’s Fast Break community, which focuses on fantasy basketball sports games. Two different levels of analyses—the individual and community level—allowed us to examine individual reflection on game strategy and decision-making as well as characteristics of the community and patterns of interactions between participants within community. The description of our use of these two analytical methods can help researchers and designers who may be attempting to analyze and characterize other large-scale virtual communities.