Challenges of Analyzing Informal Virtual Communities

Challenges of Analyzing Informal Virtual Communities

Nancy Poon, Ben K. Daniel
Copyright: © 2011 |Pages: 9
DOI: 10.4018/978-1-60960-040-2.ch035
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Abstract

Drawing from previous research, this chapter presents major challenges associated with the analysis of interaction patterns in informal virtual communities. Using social network as well as content analysis to understand the structure and nature of interaction in such virtual communities, the goal was understand the physical structure of the community as well as the nature of the themes discussed by community members in an attempt to build a theoretical model of interactions.
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Many methods have been employed for studying virtual communities and range from empirically based methods to those which are more theoretical. Similar to work conducted by De Laat (2002), we used social network analysis (SNA) to analyze interaction patterns in virtual communities. SNA seeks to understand community member networks, and to ascertain members’ relative social locations in the network or community.

A social network is a set of individuals who are connected to one another through socially meaningful relationships (Hanneman, & Mark, 2005; Freemen, 2004). Before moving onto a discussion of social network analysis nomenclature that is relevant to this chapter, a tabular comparison of formal and informal virtual communities can be found in Table 1 below.

Table 1.
Characteristics of informal and formal virtual communities
     Characteristics     Formal virtual communities     Informal virtual communities
     Membership     Stable     Some variation
     Goals     Explicit     May be implicit
     Supporting technologies     Asynchronous and synchronous     Mainly synchronous but some asynchronous technologies may apply
     Social protocols     Explicitly defined     Implied or might not exist
     Growth     Planned and stable growth     Unplanned growth, may die without warning
     Type of Awareness     Professional, demographic, tasks, and social awareness     Might vary
     Trust level     Tends to be high     Might be difficult to determine
     Discourse directions     Moderated     Might not be moderated
     Ownership     Institutional     Open
     Nature of data     Cleaned     Noisy
     Social networking     Strong     May be weakened due to anonymity
     Privacy     Safe     May be threatened

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