%0 Journal Article
%T Exploring the political pulse of a country using data science tools
%A Folgado, M. G.
%A Sanz, V.
%J Journal of Computational Social Science
%D 2022
%V 5
%I Springernature
%@ 2432-2717
%G English
%F Folgado+Sanz2022
%O WOS:000742263500002
%O exported from refbase (https://references.ific.uv.es/refbase/show.php?record=5077), last updated on Wed, 25 May 2022 07:36:16 +0000
%X 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.
%K Politics
%K Spain
%K Sentiment analysis
%K Artificial Intelligence
%K Machine learning
%K Neural networks
%K Natural Language Processing (NLP)
%R 10.1007/s42001-021-00157-1
%U https://arxiv.org/abs/2011.10264
%U https://doi.org/10.1007/s42001-021-00157-1
%P 987-1000