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This study utilizes large language models to quantify narrative polarization within partisan information environments regarding the Israeli-Palestinian conflict, distinguishing between video content and comment sections. By formalizing how narratives shape opinions independent of direct human interaction, the research offers a methodological advance for analyzing societal impacts through AI-driven discourse analysis.
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Measuring Narrative Polarization in Online Discourse

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arXiv:2601.07398v2 Announce Type: replace-cross Abstract: Polarization research has demonstrated how people cluster in homogeneous groups with opposing opinions. However, this effect emerges not only through interaction between people, limiting communication between groups, but also between narratives, shaping opinions and partisan identities. Yet, how polarized information environments portray opposing interpretations of reality, and whether narratives move between content environments despite limited interactions, remains unexplored. To address this gap, we formalize the concept of narrative polarization and demonstrate its measurement in 212 YouTube videos and 90,029 comments on the Israeli-Palestinian conflict. Based on structural narrative theory and implemented through a large language model, we extract the narrative roles assigned to central actors in two partisan information environments. We find that while videos produce highly polarized narratives, comments exhibit significantly lower levels of narrative polarization, converging on shared core narrative structures. However, recurring narrative motifs capturing more complex actor constellations reveal additional differences between partisan environments.

Abstract:Polarization research has demonstrated how people cluster in homogeneous groups with opposing opinions. However, this effect emerges not only through interaction between people, limiting communication between groups, but also between narratives, shaping opinions and partisan identities. Yet, how polarized information environments portray opposing interpretations of reality, and whether narratives move between content environments despite limited interactions, remains unexplored. To address this gap, we formalize the concept of narrative polarization and demonstrate its measurement in 212 YouTube videos and 90,029 comments on the Israeli-Palestinian conflict. Based on structural narrative theory and implemented through a large language model, we extract the narrative roles assigned to central actors in two partisan information environments. We find that while videos produce highly polarized narratives, comments exhibit significantly lower levels of narrative polarization, converging on shared core narrative structures. However, recurring narrative motifs capturing more complex actor constellations reveal additional differences between partisan environments.

Computers and Society (cs.CY); Computation and Language (cs.CL); Social and Information Networks (cs.SI)

arXiv:2601.07398 [cs.CY]

(or arXiv:2601.07398v2 [cs.CY] for this version)

https://doi.org/10.48550/arXiv.2601.07398 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1093/pnasnexus/pgag270 Focus to learn more DOI(s) linking to related resources

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