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

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 b...

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Bibliographic Details
Published inarXiv.org
Main Authors Pérez, Juan Manuel, Rajngewerc, Mariela, Giudici, Juan Carlos, Furman, Damián A, Luque, Franco, Laura Alonso Alemany, Martínez, María Vanina
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 13.07.2024
Subjects
Data mining
Python
Sentiment analysis
Social networks
Toolkits
User generated content
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Summary: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.
ISSN:2331-8422