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Political science is diverse in its methods, theories, and substantive interests. A quick perusal of our flagship journals reveals just how heterogeneous we are, with articles ranging from mathematical treatments of theoretical problems to textual exegesis of Plato, and qualitative studies of single countries standing in contrast to quantitative analyses of experiments designed to mobilize voters. At times, the discipline's boundaries are so fuzzy that our territory is alternatively claimed by philosophers, anthropologists, economists, sociologists, and psychologists.

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.

Investigations of American politics have increasingly turned to analyses of political networks to understand public opinion, voting behavior, the diffusion of policy ideas, bill sponsorship in the legislature, interest group coalitions and influence, party factions, institutional development, and other empirical phenomena. While the association between political networks and political behavior is well established, clear causal inferences are often difficult to make. This article consists of five independent essays that address practical problems in making causal inferences from studies of political networks. They consider egocentric studies of national probability samples, sociocentric studies of political communities, measurement error in elite surveys, field experiments on networks, and triangulating on causal processes.

Political networks are an important feature of the political and economic landscape of countries. Despite their ubiquity and significance, information on such networks has proven hard to collect due to a pervasive lack of transparency. However, with the advent of big data and artificial intelligence, major financial services institutions are now actively collating publicly available information on politically exposed persons and their networks. In this study, we use one such data set to show how network characteristics vary across political systems. We provide results from more than 150 countries and show how the format of the network tends to reflect the extent of democratisation of each country. We also outline further avenues for research using such data.