Mixed Methods Social Network Analysis : Theories and Methodologies in Learning and Education book cover
1st Edition

Mixed Methods Social Network Analysis
Theories and Methodologies in Learning and Education

ISBN 9780367174453
Published December 24, 2019 by Routledge
280 Pages - 33 B/W Illustrations

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Book Description

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.

Table of Contents



1. MMSNA: An Introduction of a Tale of Two Communities Dominik E. Froehlich, Martin Rehm, and Bart C. Rienties

SECTION 1: Why Do Mixed Methods Social Network Analysis?

2. Mapping Mixed Methods Approaches to Social Network Analysis in Learning and Education Dominik E. Froehlich

3. Data Collection for Mixed Method Approaches in Social Network Analysis Manuel Längler, Jasperina Brouwer, and Hans Gruber

4. Integrating Units of Analysis Dominik E. Froehlich, Mathias Mejeh, Sarah Galey, and Judith Schoonenboom

5. Visual Methods and Representations in Mixed Methods (and) Social Network Research: A Discussion Peggy Shannon-Baker and Jonathan C. Hilpert

6. Minding the Gap Between Culture and Connectivity: Laying the Foundations for A Relational Mixed Methods Social Network Analysis Petter Törnberg and Anton Törnberg

7. Ethnographic Mixed Methods Social Network Analysis Research: Convergence, Opportunities, and Challenges Marc Sarazin

8. Mixed Methods Social Network Analysis to Drive Organizational Development Tuire Palonen and Dominik E. Froehlich

9. Identity Development Through Interactions in Social Networks: A Complex Systems Approach Judith Schoonenboom

SECTION 2: How Do We Do Mixed Methods Social Network Analysis?

10. Social Network Analysis and Activity Theory: A Symbiotic Relationship Victoria L. Murphy, Allison Littlejohn, and Bart C. Rienties

11. Exploring Social Relationships in "A Mixed Way": Mixed Structural Analysis Dominik E. Froehlich

12. Unpacking the Collegial Network Structure of Beginning Teachers’ Primary School Teams: A Mixed Method Social Network Study Laura Thomas, Melissa Tuytens, Geert Devos, Geert Kelchtermans, and Ruben Vanderlinde

13. Around and Around: The Concentric Circles Method as A Powerful Tool to Collect Mixed Method Network Data Sara Van Waes and Piet Van Den Bossche

14. Reflections About Intersecting Mixed Methods Research with Social Network Analysis Sinem Toraman and Vicki L. Plano Clark

15. The Role of Knowing and Valuing Others’ Expertise in Accelerating Information Exchange Katerina Bohle Carbonell, Chris Marcum, Karen D. Könings, Patricia M. Stassen, Mien Segers, and Jeroen Van Merriënboer

16. Is Mixed Methods Social Network Analysis Ethical? Maina Korir, Jenna Mittelmeier, and Bart C. Rienties

17. Automation and The Journey to Mixed Methods Social Network Analysis Dominik E. Froehlich, Christoforos Mamas, and Herwig W. Schneider

18. Power to the People?! Twitter Discussions On (Educational) Policy Processes Martin Rehm, Frank Cornelissen, Ad Notten, Alan Daly, and Jonathan Supovitz

19. The PRICE of Mixed Methods Social Network Analysis: Toward an Ethical Process for MMSNA Anthony J. Onwuegbuzie

20. Powers and Limitations of MMSNA: Critical Reflections and Moving Forward Bart C. Rienties


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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.