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2 - Multimodal Graphs and Matrices

Published online by Cambridge University Press:  12 May 2021

David Knoke
Affiliation:
University of Minnesota
Mario Diani
Affiliation:
University of Trento, Italy
James Hollway
Affiliation:
Graduate Institute of International and Development Studies, Geneva
Dimitris Christopoulos
Affiliation:
MU Vienna and Edinburgh Business School
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Summary

Chapter 2 is methodological, offering a primer on multimodal network analysis. It proceeds by quickly reviewing 1-mode network analysis, paying special attention to summarizing several measures of network centrality and how they relate to power. Often, relational data that are 2-mode or multimodal are “projected” into one of the node sets. Ties are then defined by their shared relations to the second-mode nodes so that 1-mode measures of centrality and algorithms for community detection can be employed. We discuss the loss of information on structure and agency that projection entails and argue that, in many cases, projection is neither helpful nor necessary. We then proceed to detailed discussions of methods for 2-mode and 3-mode network analysis, from first principles of matrix algebra to centrality measures and core-periphery analysis; faction analysis and community detection; as well as structural/regular equivalence and blockmodeling. We conclude with a brief introduction to recent advances in statistical network modelling that facilitate inferences about multimodal networks.

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Publisher: Cambridge University Press
Print publication year: 2021

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