Sentiment Analysis and Multiple Means Comparison for the 2020 United States Elections

Authors

  • M. Beatriz Bernábe-Loranca Benemérita Universidad Autónoma de Puebla
  • Rogelio González-Velázquez Benemérita Universidad Autónoma de Puebla
  • Alberto Carrillo-Canán Benemérita Universidad Autónoma de Puebla
  • Erika Granillo-Martínez Benemérita Universidad Autónoma de Puebla

DOI:

https://doi.org/10.13053/cys-26-1-4155

Keywords:

Dictionary, Twitter, NLP, Python

Abstract

Here comes the abstract. Considering that the presidential elections between Trump and Biden have represented a great impact not only for the United States but also for the world and Mexico, in this work electoral preferences were analyzed using a natural language processing tool known as Sentiment Analysis. The methodology begins with reviewing and categorizing comments related to the 2020 US elections on the social network Twitter. Subsequently, the dictionaries are created to start with the sentiment analysis. In this way, three lines of analysis are established, being reflected in the following way: 1) data collection in the electoral campaign (information retrieval through downloads), 2) creation of dictionaries and 3) sentiment analysis. According to the previous order, first Tweets from different users have been randomly downloaded with the tagging algorithm, considering the comments of the Twitter attendees. The information seen as a corpus led to the definition of dictionaries and consequently, sentiment analysis bifurcates the information into two classes. Such categories have been called praise and name calling for convenience for the purposes of this article. Finally, the frequency of the terms is analyzed with descriptive and inferential statistics using the Fisher mean comparison.

Downloads

Published

2022-03-26

Issue

Vol. 26 No. 1 (2022): Recent Advances in Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez, D. Vilariño)

Section

Articles of the Thematic Issue

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.