- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
The study of social networks has attracted much interest from the IS community in recent years, driven mainly by the accessibility of trace data that remain as a by-product of interactions conducted through technology-enabled platforms. Despite its rapidly growing influence, we have some concerns about the current trajectory of social network research in the IS field. Our purpose in this commentary piece is to accentuate for the new generation of social network researchers, who are au fait with mathematical techniques for analyzing massive digital datasets, how the combination of quantitative and qualitative approaches can enrich our understanding of networks. First we highlight how the social network perspective has contributed to our understanding of IS phenomena. Next we review mixed methods research in IS social network research. An agenda for future IS social network research is then presented where we suggest how qualitative approaches can best complement trace data in addressing focal social network questions. We conclude by discussing the challenges of conducting mixed method studies of digitally enabled social networks.
The availability of extensive sources of social network data create rich opportunities for IS research. It can provide invaluable insights and allow us to develop sophisticated methods. It also creates the impetus and basis for engaging fundamental questions about how technology affects the way individuals experience the social worlds in which they live and how IT shapes, and reshapes, the larger social world around us. However, to truly exploit these opportunities IS research needs to broaden its horizons. We need to fully leverage foundational studies from sociology and anthropology and have clear conceptualizations how meaning can be extrapolated from the study of online network structures. We see a potential danger facing the field. In a race to analyze the biggest dataset of nodes and edges with the most sophisticated quantitative techniques, IS researchers may fail to fully appreciate the theoretical richness and conceptual depth of the social network tradition, and disregard the value of qualitative research approaches. The challenges we identify are certainly not insurmountable for the network researcher intending to extract insight from large sets of digital trace data. Interpretative research approaches are well suited to providing the rich and deep insights needed to describe and analyze the organizational impacts of technology mediated social networks, and the technical, economic and behavioral challenges they face. In this paper, we have articulated the enormous potential for interpretive research, particularly when combined with digital trace data, and identified the challenges that IS researchers need to address when contemplating such studies. Our hope is that doing so will help stimulate a greater appreciation for the social network tradition and how the combination of trace data and interpretive approaches can advance our understanding of social networks constructed on technology platforms.