Target-Oriented Polarity Classification of Opinion in Comments about Political Debate in Portuguese

• Eloize R. Marques Seno IFSP http://orcid.org/0000-0002-1549-9794
• Fábio S. Igarashi Anno IFSP
• Lucas Lazarini IFSP
• Helena M. Caseli UFSCar http://orcid.org/0000-0003-3996-8599

DOI: https://doi.org/10.5753/stil.2023.233938

Abstract

The internet and, especially social media, are fertile ground for publishing opinions on various subjects, products, and services. Traditionally, automatic analysis of opinions has been based on words that denote polarity or emotion. However, with the emergence of large language models like ChatGPT, the way in which we process text for subjective analysis has changed a lot. In this context, this paper aims to investigate the potential of ChatGPT – compared to a neural model for emotion identification in texts, and lexicon-based approaches – in polarity classification oriented towards opinion targets in comments on political debate in Portuguese.

Keywords: Sentiment Analysis, Polarity Classification, Political Domain, Portuguese

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