SentiProdBR: Building Domain-Specific Sentiment Lexicons for the Portuguese Language
Resumo
Online reviews are readily available on the Web and widely used for decision-making. However, only a few studies on Portuguese sentiment analysis are reported due to the lack of resources including domain-specific sentiment lexical collections. In this paper, we present an effective methodology using probabilities of the Bayes’ Theorem for building a set of lexicons, called SentiProdBR, for 10 different product categories for the Portuguese language. Experimental results indicate that our methodology significantly outperforms several alternative approaches of building domain-specific sentiment lexicons.
Palavras-chave:
Sentiment Lexicons, Sentiment Analysis, Natural Language Processing
Referências
Almatarneh, S. and Gamallo, P. (2018). A lexicon based method to search for extreme opinions. PLOS ONE, 13(5):1–19.
Deng, S., Sinha, A. P., and Zhao, H. (2017). Adapting sentiment lexicons to domain-specific social media texts. Decision Support Systems, 94:65–76.
Freitas, C. (2013). Sobre a construção de um léxico da afetividade para o processamento computacional do português. Revista Brasileira de Linguística, 13(4):1031–1059.
Huang, M., Xie, H., Rao, Y., Feng, J., and Wang, F. L. (2020). Sentiment strength detection with a context-dependent lexicon-based convolutional neural network. Information Sciences, 520:389–399.
Labille, K., Alfarhood, S., and Gauch, S. (2016). Estimating sentiment via probability and information theory. KDIR, 2016:121–129.
Labille, K., Gauch, S., and Alfarhood, S. (2017). Creating domain-specific sentiment lexicons via text mining. In Workshop Issues Sentiment Discovery Opinion Mining, pages 1–8.
Pereira, D. A. (2021). A survey of sentiment analysis in the portuguese language. Artificial Intelligence Review, 54(2):1087–1115.
Souza, M. and Vieira, R. (2011). Construction of a portuguese opinion lexicon from multiple resources. Simpósio Brasileiro de TI e da Linguagem Humana.
Vilares, D., Peng, H., Satapathy, R., and Cambria, E. (2018). Babelsenticnet: a commonsense reasoning framework for multilingual sentiment analysis. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1292–1298. IEEE.
Xiang, R., Jiao, Y., and Lu, Q. (2019). Sentiment augmented attention network for cantonese restaurant review analysis. In Proceedings of WISDOM’19: Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM’19).
Deng, S., Sinha, A. P., and Zhao, H. (2017). Adapting sentiment lexicons to domain-specific social media texts. Decision Support Systems, 94:65–76.
Freitas, C. (2013). Sobre a construção de um léxico da afetividade para o processamento computacional do português. Revista Brasileira de Linguística, 13(4):1031–1059.
Huang, M., Xie, H., Rao, Y., Feng, J., and Wang, F. L. (2020). Sentiment strength detection with a context-dependent lexicon-based convolutional neural network. Information Sciences, 520:389–399.
Labille, K., Alfarhood, S., and Gauch, S. (2016). Estimating sentiment via probability and information theory. KDIR, 2016:121–129.
Labille, K., Gauch, S., and Alfarhood, S. (2017). Creating domain-specific sentiment lexicons via text mining. In Workshop Issues Sentiment Discovery Opinion Mining, pages 1–8.
Pereira, D. A. (2021). A survey of sentiment analysis in the portuguese language. Artificial Intelligence Review, 54(2):1087–1115.
Souza, M. and Vieira, R. (2011). Construction of a portuguese opinion lexicon from multiple resources. Simpósio Brasileiro de TI e da Linguagem Humana.
Vilares, D., Peng, H., Satapathy, R., and Cambria, E. (2018). Babelsenticnet: a commonsense reasoning framework for multilingual sentiment analysis. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1292–1298. IEEE.
Xiang, R., Jiao, Y., and Lu, Q. (2019). Sentiment augmented attention network for cantonese restaurant review analysis. In Proceedings of WISDOM’19: Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM’19).
Publicado
04/10/2021
Como Citar
DE MELO, Tiago.
SentiProdBR: Building Domain-Specific Sentiment Lexicons for the Portuguese Language. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 36. , 2021, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 349-354.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2021.17897.
