Analysing qualitative data from virtual worlds: using images and text mining

There is an increasing interest within both organisational and social contexts in virtual worlds and virtual reality platforms. Virtual worlds are highly graphical systems in which avatars interact with each other, and almost every event and conversation is logged and recorded. This presents new challenges for qualitative researchers in information systems. This paper addresses the challenges of analyzing the huge amounts of qualitative data that can be obtained from virtual worlds (both images and text). It addresses how images might be used in qualitative studies of virtual worlds, and proposes a new way to analyze textual data using a qualitative software tool called Leximancer. This paper illustrates these methods using a study of a social movement in a virtual world.