Work

Sentiment Analysis in Portuguese Texts from Online Health Community Forums: Data, Model and Evaluation

Year: 2021

Type: conference-paper

Abstract: This study introduces novel data and models for the task of Sentiment Analysis in Portuguese texts about Diabetes Mellitus. The corpus contains 1290 posts retrieved from online health community forums in Portuguese and annotated by two annotators according to 3 sentiment categories (e.g. Positive, Neutral and Negative). Evaluation of traditional (Support Vector Machine, Decision Tree, Random Forest and Logistic Regression classifiers) and state-ofthe-art (BERT-based models) machine learning classifiers for the task showed the advantage in performance of the latter models as expected. Data and models are available to the community upon request.

Source: Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL)

DOI: 10.5753/stil.2021.17785

Authors: Yohan Bonescki Gumiel, Isabela Lee, Tayane Arantes Soares, Thiago Castro Ferreira, Adriana Pagano

Institutions: Universidade Federal de Minas Gerais, Pontifical Catholic University of Puerto Rico, Pontifícia Universidade Católica do Paraná

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4200380281

FWCI: 0.466

Cites: 18

Cited by: 5

Related to: 10