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Author  |
Ansia Dibuja, D.; Folgado, M.G.; Sanz, V. |
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Title |
Analyzing polarization among Spanish political elites using machine learning techniques |
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Journal Article |
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Year |
2026 |
Publication |
Journal of Computational Social Science |
Abbreviated Journal |
J. Comput. Soc. Sci. |
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Volume |
9 |
Issue |
1 |
Pages |
4 - 26pp |
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Keywords |
Political polarisation; Parliamentary corpus; Elite polarisation; Ideological placement; Affective polarisation; Ideological polarisation; Sentiment analysis; NLP; Document embeddings; Spain; Congreso de los Diputados; Data science |
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Abstract |
This study analyzes ideological and affective polarisation in the Spanish Parliament from 2000 to 2022 using Natural Language Processing (NLP) techniques. Parliamentary records were harvested, pre-processed, and analyzed with document embeddings to assess ideological polarisation, and with sentiment analysis models (VADER and Transformer-based) to measure affective polarisation. The findings reveal a significant increase in both ideological and affective divisions, particularly in recent legislative terms. This research contributes new tools for mapping political discourse and provides a rich, publicly available dataset to support further studies on Spanish political elites. |
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Address |
[Dibuja, Daniel Ansia] Tech Univ Denmark DTU, Lyngby, Denmark, Email: daniel.ansia@gmail.com; |
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Publisher |
Springernature |
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Language |
English |
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Original Title |
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Series Volume |
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Edition |
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ISSN |
2432-2717 |
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Notes |
WOS:001611306500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
7048 |
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