Mixed Methods Social Network Analysis

Mixed Methods Social Network Analysis brings together diverse perspectives from 42 international experts on how to design, implement, and evaluate mixed methods social network analysis (MMSNA). There is an increased recognition that social networks can be important catalysts for change and transformation.

This edited book from leading experts in mixed methods and social network analysis describes how researchers can conceptualize, develop, mix, and intersect diverse approaches, concepts, and tools. In doing so, they can improve their understanding and insights into the complex change processes in social networks. Section 1 includes eight chapters that reflect on "Why should we do MMSNA?", providing a clear map of MMSNA research to date and why to consider MMSNA. In Section 2 the remaining 11 chapters are dedicated to the question "How do I do MMSNA?", illustrating how concentric circles, learning analytics, qualitative structured approaches, relational event modeling, and other approaches can empower researchers.

This book shows that mixing qualitative and quantitative approaches to social network analysis can empower people to understand the complexities of change in networks and relations between people. It shows how mixed analysis can be applied to a wide range of data generated by diverse global communities: American school children, Belgian teachers, Dutch medical professionals, Finnish consultants, French school children, and Swedish right-wing social media users, amongst others. It will be of great interest to researchers and postgraduate students in education and social sciences and mixed methods scholars.

Dominik E. Froehlich is a postdoctoral researcher at the Department of Education at the University of Vienna. His research focuses on mixed methods and social network analysis, as well as on (informal) learning in the workplace.

Martin Rehm is a postdoctoral research fellow at the University of Education in Weingarten, Germany. He also holds the position of Transfermanager for the Institute for Educational Consultancy at the same university.

Bart C. Rienties leads the Open University's innovative efforts in learning analytics as program director. His research interests include a range of social influences on education, such as collaborative use of educational technology, the role of motivation in learning, and internationalization in higher education.