Predicting the Usefulness of Online Product Reviews in Brazilian Portuguese Language
Abstract
With the growth of e-commerce, online product reviews have become a significant factor in influencing users' purchasing decisions. However, users may be harmed by the information overload on online review platforms. In this study, we evaluate different approaches to identify helpful product reviews. To achieve this, a large dataset of Amazon reviews from various product domains was proposed. The results demonstrate that it is possible to predict the usefulness of online reviews without relying on any handcrafted features.
Keywords:
User Reviews Helpfulness Prediction, Natural Language Processing, Machine Learning
References
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ElKafrawy, P., Mahgoub, A., Atef, H., Nasser, A., Yasser, M., Medhat, W. M., and Darweesh, M. S. (2023). Sentiment analysis: Amazon electronics reviews using bert and textblob. https://doi.org/10.1109/ESOLEC54569.2022.10009176 https://ieeexplore.ieee.org/document/10009176
Henrickson, K., Rodrigues, F., and Pereira, F. C. (2019). Chapter 5 - Data Preparation. In Antoniou, C., Dimitriou, L., and Pereira, F., editors, Mobility Patterns, Big Data and Transport Analytics, pages 73–106. Elsevier.
Senecal, S., Kalczynski, P., and Nantel, J. (2005). Consumers’ decision-making process and their online shopping behavior: A clickstream analysis. Journal of Business Research, pages 1599–1608. https://doi.org/10.1016/j.jbusres.2004.06.003 [link].
Souza, F., Nogueira, R., and Lotufo, R. (2020). Bertimbau: Pretrained bert models for brazilian portuguese. In Intelligent Systems: 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20–23, 2020, Proceedings, Part I, page 403–417, Berlin, Heidelberg. Springer-Verlag. https://doi.org/10.1007/978-3-030-61377-8_28 [link].
Tonkin, E. L. (2016). Chapter 2 - A Day at Work (with Text): A Brief Introduction. In Tonkin, E. L. and Tourte, G. J. L., editors, Working with Text, Chandos Information Professional Series, pages 23–60. Chandos Publishing. https://doi.org/10.1016/B978-1-84334-749-1.00002-0 [link].
Tufchi, S., Yadav, A., Rai, V. K., and Banerjee, A. (2023). Sentiment analysis on amazon product review: A comparative study. In Khanna, A., Polkowski, Z., and Castillo, O., editors, Proceedings of Data Analytics and Management, pages 139–149, Singapore. Springer Nature Singapore. https://doi.org/10.1007/978-981-19-7615-5_13 [link].
Published
2023-09-25
How to Cite
BRITTO, Larissa F. S.; PACÍFICO, Luciano D. S.; LUDERMIR, Teresa B..
Predicting the Usefulness of Online Product Reviews in Brazilian Portuguese Language. In: BRAZILIAN SYMPOSIUM IN INFORMATION AND HUMAN LANGUAGE TECHNOLOGY (STIL), 14. , 2023, Belo Horizonte/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 235-239.
DOI: https://doi.org/10.5753/stil.2023.234226.
