A combination of lexicon-based and classified-based methods for sentiment classification based on Bert

Zhang, Jiaxin (2021) A combination of lexicon-based and classified-based methods for sentiment classification based on Bert. Journal of Physics: Conference Series, 1802 (3). 032113. ISSN 1742-6588 (https://doi.org/10.1088/1742-6596/1802/3/032113)

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Abstract

Abstract: Sentiment classification is a crucial problem in natural language processing and is essential to understand user opinions. There are two main approaches to solve this problem, one is the classified-based method, the other is the lexicon-based method; however, both methods perform not well on the long-sequence methods, and each method has its advantages and disadvantages. This paper introduced a new method called Lexiconed BERT, which cream off the best and filter out the impurities from the above two methods. The evaluation shows that our model achieves excellent results in the long sequence sentence and reduce resource consumption significantly.

ORCID iDs

Zhang, Jiaxin ORCID logoORCID: https://orcid.org/0000-0001-7355-7975;
CORE (COnnecting REpositories)