Unveiling Affective Polarization Trends in Parliamentary Proceedings

Abstract Recent years have seen an increase in polarized discourse worldwide, on various platforms. We propose a novel method for quantifying polarization, based on the emotional style of the discourse rather than on differences in ideological stands. Using measures of Valence, Arousal and Dominance, we detect signals of emotional discourse and use them to operationalize the concept of affective polarization. Applying this method to a recently released corpus of proceedings of the Knesset, the Israeli parliament (in Hebrew), we find that the emotional style of members of government differs from that of opposition members; and that the level of affective polarization, as reflected by this style, is significantly increasing with time.

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Publication Details

Journal
Computational Linguistics
Published
2026-01-06
DOI
https://doi.org/10.1162/coli.a.600
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00

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article

Unveiling Affective Polarization Trends in Parliamentary Proceedings

Shuly Wintner, Gili Goldin, Ella Rabinovich
Computational Linguistics
Sentiment Analysis and Opinion Mining
article

Unveiling Affective Polarization Trends in Parliamentary Proceedings

Shuly Wintner, Gili Goldin, Ella Rabinovich
article en

Abstract

Abstract Recent years have seen an increase in polarized discourse worldwide, on various platforms. We propose a novel method for quantifying polarization, based on the emotional style of the discourse rather than on differences in ideological stands. Using measures of Valence, Arousal and Dominance, we detect signals of emotional discourse and use them to operationalize the concept of affective polarization. Applying this method to a recently released corpus of proceedings of the Knesset, the Israeli parliament (in Hebrew), we find that the emotional style of members of government differs from that of opposition members; and that the level of affective polarization, as reflected by this style, is significantly increasing with time.

Computational Linguistics
Academic College of Tel Aviv-Yafo (IL), University of Haifa (IL)
University of Haifa
Openalex Percentile: Top 99%
Sentiment Analysis and Opinion Mining
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