pysentimiento: A Python Toolkit for Opinion Mining and Social NLP tasks

Juan Manuel Pérez; Mariela Rajngewerc; Juan Carlos Giudici; Damián A. Furman; Franco Luque; Laura Alonso Alemany; María Vanina Martínez

arXiv · 2106.09462

pysentimiento: A Python Toolkit for Opinion Mining and Social NLP tasks

Juan Manuel Pérez·Mariela Rajngewerc·Juan Carlos Giudici·Damián A. Furman·Franco Luque·Laura Alonso Alemany·María Vanina Martínez

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Abstract

In recent years, the extraction of opinions and information from user-generated text has attracted a lot of interest, largely due to the unprecedented volume of content in Social Media. However, social researchers face some issues in adopting cutting-edge tools for these tasks, as they are usually behind commercial APIs, unavailable for other languages than English, or very complex to use for non-experts. To address these issues, we present pysentimiento, a comprehensive multilingual Python toolkit designed for opinion mining and other Social NLP tasks. This open-source library brings state-of-the-art models for Spanish, English, Italian, and Portuguese in an easy-to-use Python library, allowing researchers to leverage these techniques. We present a comprehensive assessment of performance for several pre-trained language models across a variety of tasks, languages, and datasets, including an evaluation of fairness in the results.

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Juan Manuel Pérez, Mariela Rajngewerc, Juan Carlos Giudici, Damián A. Furman, Franco Luque, Laura Alonso Alemany, María Vanina Martínez. 2021-06-17. pysentimiento: A Python Toolkit for Opinion Mining and Social NLP tasks. https://arxiv.org/abs/2106.09462

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