Satisfaction Analysis of Brazilian Services and Products on Electronic Platforms: A Text Mining Approach

• Isabella Lopes Carmo dos Santos Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
• Marcos V. Villas Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
• Sergio Lifschitz Pontifical Catholic University of Rio de Janeiro (PUC-Rio) https://orcid.org/0000-0003-3073-3734

DOI: https://doi.org/10.5753/sbbd_estendido.2024.243794

Abstract

This article presents the development of a methodology to understand consumers' opinions and feelings after providing services and selling products on Brazilian electronic platforms, using text mining techniques. The study focuses on topic modeling, sentiment analysis, and named entity extraction from consumer comments. The method was applied to public evaluation data from different sectors, aiming to help companies and traders improve their products, services and customer service. Furthermore, the article discusses the challenges faced, including handling the selected techniques and evaluating the results of the methodology. The final construction of the method demonstrates its effectiveness in understanding customer satisfaction in different sectors, providing relevant insights.

Keywords: Customer Satisfaction, Text Mining, Electronic Platforms, Methodology, Data Science

References

Blei, D. M., Ng, A. Y., and Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3.

Caro, L. M. and Garcia, J. A. M. (2007). Measuring perceived service quality in urgent transport service. Journal of Retailing and Consumer Services, 14(1).

Kherwa, P. and Bansal, P. (2019). Topic modeling: a comprehensive review. EAI Endorsed transactions on scalable information systems, 7(24).

Lyu, F. and Choi, J. (2020). The forecasting sales volume and satisfaction of organic products through text mining on web customer reviews. Sustainability, 12(11).

Silva, F. M. (2022). Proposta de um índice de avaliação da satisfação do uso do transporte público do município de são carlos por meio da adaptação do customer satisfaction score. Repositório Intistucional UFSCAR.

Souza, F. D. and de Oliveira e Souza, J. B. (2021). Sentiment analysis on brazilian portuguese user reviews. IEEE Latin American Conference on Computational Intelligence (LA-CCI).