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Male and female politicians on Twitter: A machine learning approach

Author
Beltran, J.; Gallego, A.; Huidobro, A.; Romero, E.; Padro, L.
Type of activity
Journal article
Journal
European journal of political research
Date of publication
2021-02
Volume
60
Number
1
First page
239
Last page
251
DOI
10.1111/1475-6765.12392
Repository
http://hdl.handle.net/2117/187901 Open in new window
URL
https://ejpr.onlinelibrary.wiley.com/doi/epdf/10.1111/1475-6765.12392 Open in new window
Abstract
How does the language of male and female politicians differ when they communicate directly with the public on social media? Do citizens address them differently? We apply Lasso logistic regression models to identify the linguistic features that most differentiate the language used by or addressed to male and female Spanish politicians. Male politicians use more words related to politics, sports, ideology, and infrastructure, while female politicians talk about gender and social affairs. The choi...
Citation
Beltran, J. [et al.]. Male and female politicians on Twitter: A machine learning approach. "European journal of political research", Febrer 2021, vol. 60, núm. 1, p. 239-251.
Keywords
Gender differences, Machine learning, Politicians, Social media, Twitter
Group of research
GPLN - Natural Language Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
SOCO - Soft Computing
TALP - Centre for Language and Speech Technologies and Applications

Participants