Extracting narrative signals from public discourse: a network-based approach

Armin Pournaki () and Tom Willaert
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Armin Pournaki: Max Planck Institute for Mathematics in the Sciences
Tom Willaert: Vrije Universiteit Brussel, Brussels School of Governance

Humanities and Social Sciences Communications, 2025, vol. 12, issue 1, 1-16

Abstract: Abstract Narratives are key interpretative devices by which humans make sense of political reality. As the significance of narratives for understanding current societal issues such as polarization and misinformation becomes increasingly evident, there is a growing demand for methods that support their empirical analysis. To this end, we propose a graph-based formalism and machine-guided method for extracting, representing, and analyzing selected narrative signals from digital textual corpora, based on Abstract Meaning Representation (AMR). The formalism and method introduced here specifically cater to the study of political narratives that figure in texts from digital media such as archived political speeches, social media posts, transcripts of parliamentary debates, and political manifestos on party websites. We conceptualize these political narratives as a type of ontological narratives: stories by which actors position themselves as political beings, and which are akin to political worldviews in which actors present their normative vision of the world, or aspects thereof. We approach the study of such political narratives as a problem of information retrieval: starting from a textual corpus, we first extract a graph-like representation of the meaning of each sentence in the corpus using AMR. Drawing on transferable concepts from narratology, we then apply a set of heuristics to filter these graphs for representations of (1) actors and their relationships, (2) the events in which these actors figure, and (3) traces of the perspectivization of these events. We approach these references to actors, events, and instances of perspectivization as core narrative signals that allude to larger political narratives. By systematically analyzing and re-assembling these signals into networks that guide the researcher to the relevant parts of the text, the underlying narratives can be reconstructed through a combination of distant and close reading. A case study of State of the European Union addresses (2010–2023) demonstrates how the formalism can be used to inductively surface signals of political narratives from public discourse.

Date: 2025
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DOI: 10.1057/s41599-025-06017-x

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