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David Knoke, Mario Diani, James Hollway, Dimitris Christopoulos - Multimodal Political Networks, Inbunden

Inbunden, Engelska, 2021

Multimodal Political Networks

Av David Knoke, Mario Diani, James Hollway, Dimitris Christopoulos

Del 50 i serien Structural Analysis in the Social Sciences

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Beskrivning
Research on social networks has become a significant area of investigation in the social sciences, and social network concepts and tools are widely employed across many subfields within the field. This volume introduces political theorists and researchers to new theoretical, methodological, and substantive tools for extending political network research into new realms and revitalizing established domains. The authors synthesize new understandings of multimodal political networks, consisting of two or more types of social entities - voters, politicians, parties, events, organizations, nations - and the complex relations between them. They discuss ways to theorize about multimodal connections, methods for measuring and analyzing multimodal datasets, and how the results can reveal new insights into political structures and action. Several empirical applications demonstrate in great detail how multimodal analysts can detect and visualize political communities consisting of diverse social entities.
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David Knoke is Professor of Sociology at the University of Minnesota. Mario Diani is Professor of Sociology at the University of Trento. James Hollway is Associate Professor of International Relations/Political Science at the Graduate Institute, Geneva. Dimitris Christopoulos is Director of Research at Edinburgh Business School and Associate Professor at MU Vienna.

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'This book is a must have and must read for all policy researchers and social scientists interested in social network analysis and its application. It allows for the right mix between 'keeping complexity' to grasp the intricacies of the political game and 'reducing complexity' to come to systematic, comparative, and generalizable results. It gives essential guidelines on how to analyze two- and multi-mode networks.' Karin Ingold, University of Bern

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