Version 1
: Received: 25 October 2023 / Approved: 25 October 2023 / Online: 25 October 2023 (16:18:11 CEST)
How to cite:
Montejo-Ráez, A.; Díaz-Galiano, M. C.; Navarro-Ardoy, L.; González-Fernández, M. T. Psicolinguistic Modeling of Spanish Political Parties from Social Media. Preprints2023, 2023101671. https://doi.org/10.20944/preprints202310.1671.v1
Montejo-Ráez, A.; Díaz-Galiano, M. C.; Navarro-Ardoy, L.; González-Fernández, M. T. Psicolinguistic Modeling of Spanish Political Parties from Social Media. Preprints 2023, 2023101671. https://doi.org/10.20944/preprints202310.1671.v1
Montejo-Ráez, A.; Díaz-Galiano, M. C.; Navarro-Ardoy, L.; González-Fernández, M. T. Psicolinguistic Modeling of Spanish Political Parties from Social Media. Preprints2023, 2023101671. https://doi.org/10.20944/preprints202310.1671.v1
APA Style
Montejo-Ráez, A., Díaz-Galiano, M. C., Navarro-Ardoy, L., & González-Fernández, M. T. (2023). Psicolinguistic Modeling of Spanish Political Parties from Social Media. Preprints. https://doi.org/10.20944/preprints202310.1671.v1
Chicago/Turabian Style
Montejo-Ráez, A., Luis Navarro-Ardoy and Manuel Tomás González-Fernández. 2023 "Psicolinguistic Modeling of Spanish Political Parties from Social Media" Preprints. https://doi.org/10.20944/preprints202310.1671.v1
Abstract
This study applies several natural language processing techniques for characterizing social groups by analyzing published text in social media. The resulting computed values are proposed as features for modeling social groups and measure distances or similarities among them, along further data that could help understanding group behavior according to language usage. In this study, we have analyzed the messages published on Twitter regarding patriotism by the main political parties in Spain. The results show that lexical resources and topic modelling algorithms are useful to model different groups and serve as comparison tools to better understand the topics these groups are talking about.
Keywords
Social Computing; Topic Modeling; Psicolinguistics; Natural Language; NLP
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.