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date: 21 June 2021

Abstract and Keywords

Network analysis offers a powerful framework for analyzing traces of digital communication. Yet communication researchers have largely followed the lead of social network theorists, who do not always share the former’s analytical goals. This chapter introduces three research questions of broad interest to scholars of networked digital communication that are not easily answered with tools created by social network theorists. It answers these questions empirically using a real-world Twitter data set to demonstrate their value. It also provides a Python module that implements functions to answer these questions, as well as a supplemental tutorial that demonstrates how to use the functions.

Keywords: network analysis, trace data, Python module, homophily, polarization, fragmentation, selective exposure, social network theory

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