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Theory-Building and Tool-Building for a Science of Dysfunctional Political Discourse

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Advances in Quantitative Ethnography (ICQE 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1895))

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Abstract

This paper extends a developing analytic framework for political discourse that takes place over digital social media. Earlier presentations of the framework have furnished a rationale for applying the conceptual framework of epistemic frame theory and the tools of quantitative ethnography for political discourse analysis. They have provided early existence proofs of the viability of epistemic network analysis (ENA) for rudimentary models of social media threads that involve political content. The current theoretical paper moves significantly beyond this foundation. It summarizes and deepens the explanation of the constructs of discursive transactions, response grammars, and epistemic frames in political discourse. It proposes and supports three modeling tools for building a productive science of political discourse. The first modeling tool involves both ENA and a mathematical means for extending ENA’s key explanatory and predictive potential to display dyadic connections between constructs. The second involves complex adaptive system (CAS) theory. The third involves the application of artificial neural networks. Each of these three tools provides valuable modeling affordances which the other two do not. Collectively, these three approaches hold promise to contribute to the science of political discourse by deepening our understanding and supporting potential repair of profoundly disturbing trends in political conversations that are unfolding globally.

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Correspondence to Eric Hamilton , Marguerite Williamson or Andrew Hurford .

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Hamilton, E., Williamson, M., Hurford, A. (2023). Theory-Building and Tool-Building for a Science of Dysfunctional Political Discourse. In: Arastoopour Irgens, G., Knight, S. (eds) Advances in Quantitative Ethnography. ICQE 2023. Communications in Computer and Information Science, vol 1895. Springer, Cham. https://doi.org/10.1007/978-3-031-47014-1_19

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  • DOI: https://doi.org/10.1007/978-3-031-47014-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47013-4

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