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English Information

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Authors
# Name
1 Tiago de Melo(tmelo@uea.edu.br)

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Reference
# Reference
1 Almatarneh, S. and Gamallo, P. (2018). A lexicon based method to search for extreme opinions. PLOS ONE, 13(5):1–19.
2 Deng, S., Sinha, A. P., and Zhao, H. (2017). Adapting sentiment lexicons to domain-specific social media texts. Decision Support Systems, 94:65–76.
3 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.
4 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.
5 Labille, K., Alfarhood, S., and Gauch, S. (2016). Estimating sentiment via probability and information theory. KDIR, 2016:121–129.
6 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.
7 Pereira, D. A. (2021). A survey of sentiment analysis in the portuguese language. Artificial Intelligence Review, 54(2):1087–1115.
8 Souza, M. and Vieira, R. (2011). Construction of a portuguese opinion lexicon from multiple resources. Simp´osio Brasileiro de TI e da Linguagem Humana.
9 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.
10 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).