Peruvian Presidential Debates in the Elections of 2021 in Twitter/X: A sentiment analysis approach

Victor Andres Ayma, Juan D. Cardenas, Walter Aliaga, Victor Hugo Ayma, Aramis Palacios, Rafaela B. Sierra

Research output: Contribution to journalArticle in a journalpeer-review

Abstract

Over the years, technology has rapidly evolved, with social networks and media emerging as prominent examples. Social media facilitates the creation and exchange of content, while social networks connect individuals and organizations based on shared interests or values. Among these platforms, Twitter (now X) has gained significant attention and has been a valuable tool for monitoring reputation and brands, including political discourse. With the widespread use of social networks, the demand for advanced textual data analysis techniques, particularly sentiment analysis, has grown. Sentiment analysis, or polarity classification, aims to gauge the positivity or negativity of textual content, providing information on public opinion dynamics. In the context of the Peruvian presidential elections of 2021, characterized by political uncertainty exacerbated by the COVID-19 pandemic, social media platforms, especially Twitter/X, emerged as vital arenas for political discourse and participation. The election featured various candidates representing a wide spectrum of ideologies, reflecting the complexities of Peruvian society. Against this backdrop, this research uses Twitter/X data to analyze public sentiment toward presidential candidates and election-related topics. Through state-of-the-art sentiment analysis algorithms, this study categorizes tweets into positive, negative, or neutral sentiments, revealing key trends and themes driving public opinion on Twitter/X during the election period. By examining sentiment dynamics in response to major events and comparing Twitter/X sentiment trends with official voting data, the research aims to assess the predictive power of social media sentiment analysis in forecasting electoral outcomes. Therefore, this research contributes to understanding the role of social media in shaping political discourse and public opinion during elections. By conducting sentiment analysis on Twitter data, valuable insights are offered to policymakers, political analysts, and researchers who want to leverage social media to understand and forecast electoral trends.

Original languageEnglish
Pages (from-to)138386-138398
Number of pages13
JournalIEEE Access
Volume12
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Machine Learning
  • Peru
  • Presidential Elections
  • Sentiment Analysis
  • Social Network
  • Text Mining
  • Twitter/X

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