| Records |
| Author |
Folgado, M.G.; Sanz, V. |
| Title |
Exploring the political pulse of a country using data science tools |
Type |
Journal Article |
| Year |
2022 |
Publication |
Journal of Computational Social Science |
Abbreviated Journal |
J. Comput. Soc. Sci. |
| Volume |
5 |
Issue |
|
Pages |
987-1000 |
| Keywords |
Politics; Spain; Sentiment analysis; Artificial Intelligence; Machine learning; Neural networks; Natural Language Processing (NLP) |
| Abstract |
In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis. |
| Address |
[Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Valencia 46980, Spain, Email: migarfol@upvnet.upv.es; |
| Corporate Author |
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Thesis |
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| Publisher |
Springernature |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title  |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2432-2717 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000742263500002 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5077 |
| Permanent link to this record |
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| Author |
Ansia Dibuja, D.; Folgado, M.G.; Sanz, V. |
| Title |
Analyzing polarization among Spanish political elites using machine learning techniques |
Type |
Journal Article |
| Year |
2026 |
Publication |
Journal of Computational Social Science |
Abbreviated Journal |
J. Comput. Soc. Sci. |
| Volume |
9 |
Issue |
1 |
Pages |
4 - 26pp |
| 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 |
| 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. |
| Address |
[Dibuja, Daniel Ansia] Tech Univ Denmark DTU, Lyngby, Denmark, Email: daniel.ansia@gmail.com; |
| Corporate Author |
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Thesis |
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| Publisher |
Springernature |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2432-2717 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:001611306500001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
7048 |
| Permanent link to this record |
