Powers and Limitations of MMSNA: Critical Reflections and Moving Forward

As highlighted by the 20 chapters in this book, there is an increased call for SNA researchers to embrace and mix methods developed in qualitative research to understand the what, how, and why questions of social network relations. At the same time, several researchers in the qualitative domain have encouraged researchers to start to embrace some of the principles of SNA and theory. In this final chapter, I will reflect on the contributions of the authors of this book as well as my own twelve years of working with social network data and experimentations of quantitative and qualitative data methods and approaches, what has worked, and what has not. In particular, I will focus on how recent phenomena of learning analytics and big data allow researchers and practitioners tremendous opportunities to unpack the complexities of social relations and how people learn, while at the same time cautioning about potentially over-interpreting relations between people when not triangulating trace-data with attitudes, behavior, and cognition of human interaction. At the same time, I will discuss the potential limitations of SNA approaches, in particular given the complexities of mastering two ontologically different methods