In recent years, we have seen a rapid growth of online communities on the Web. These virtual communities serve as socio-technical platforms for various professionals, entrepreneurs and serious hobbyists to engage in discussion around a shared area of interest. They mostly use these platforms to exchange knowledge and expertise. So far, online communities have been analysed either via the structure of the communities or the content of messages and the motivations of members. We argue that in order to gain insight in the dynamics of online communities, we have to combine a set of methods that allows for the analysis of both the structure as well as the content of communications in these communities. Empirical studies in the domain of online communities usually employ a single method. Often, motivations to participate in these communities were investigated [e.g., 1, 2]. Other research focused on behaviour of community members [e.g., 3, 4]. Some of these studies employed qualitative methods, especially case studies [5-6] and ethnographies [7-8]. However, studies that combine different methods are scarce . This holds in particular for studies that focus on relational (using social network analysis) and interpretational information (using for example semantic maps). To our knowledge, studies that employ both methods are lacking. With this paper, we want to contribute to the literature by proposing a way to combine both approaches. We illustrate the approach with data from an online community, and discuss implications for researchers.
|Title of host publication||Proceedings of the ACM WebSci'11|
|Place of Publication||Koblenz, Germany|
|Publication status||Published - 2011|
|Event||WebSci'11 - Koblenz, Germany|
Duration: 14 Jun 2011 → 17 Jun 2011
|Period||14/06/11 → 17/06/11|