Editorial

Although the study of social networks enjoys a long and rich tradition, particularly in the fields of sociology and anthropology, it has only recently grown in popularity among information systems (IS) researchers interested in applying established social network theories to online environments. Social network theory is built on the premise that social behaviour cannot be fully understood without considering the underlying structure (i.e. the pattern of connections) of the network in which an actor is embedded. Although seminal studies have shown that social network structure explainswhy peoplemake certain political voting choices (Lazarsfeld et al., 1948), adopt particular innovations (Rogers, 1995), or get promoted faster than others (Burt 1992), the field has always struggled to validate its legitimacy due to data collection issues. Due to the increasing availability of ‘trace data’, i.e. electronic records of who interacts with whom through digitally enabled platforms such as Facebook, Twitter, and Second Life as well email, phone and wiki communications, IS researchers are now being drawn to the social network tradition. The accessibility and sheer volume of trace data sets offers the potential for deep insights into the causes and results of social behaviour that were previously not possible (Watts 2007). In response to the growing interest in digitally enabled social networks and the research advantages they afford, a number of prominent IS journals and conferences have dedicated special issues and tracks to expanding our knowledge of these platforms. The majority of studies emanating from these outlets have tended to investigate digitally enabled social networks with a positivist philosophy employing quantitative methods. As such, much of our current understanding of the dynamics of these online social structures stems from methods that measure the overall network structure and/or position of individuals within the network and that then relate these structural variables to a variety of other variables. Yet, there is still much to be understood about social networks constructed through digital platforms, and interpretative studies offer great promise in expanding our knowledge by providing rich and deep insights into the inner workings of these organising forms. The aim of this Information Systems Journal special issue is to advance the state of social network research within the IS field by disseminating empirical results gained through interpretative studies. This special issue includes four articles that were selected from the 24 initial submissions. They have proceeded through three rounds of peer review and editorial feedback from the special issue guest editors before receiving final acceptance. Our hope is that this special issue will encourage IS researchers to make greater use of qualitative data, multimethod approaches, and interpretive methods for describing and analysing social networks. A brief summary of these papers follows.