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• W2938574033 startingPage "1243" @default.
• W2938574033 abstract "Text is a typical example of unstructured and heterogeneous data in which massive useful knowledge is embedded. Sentiment analysis is used to analyze and predict sentiment polarities of the text. This paper provides a survey and gives comparative analyses of the latest articles and techniques pertaining to lexicon-based, traditional machine learning-based, deep learning-based, and hybrid sentiment analysis approaches. These approaches have their own superiority and get the state-of-the-art results on diverse sentiment analysis tasks. Besides, a brief sentiment analysis example in the tourism domain is displayed, illustrating the entire process of sentiment analysis. Furthermore, we create a large table to compare the pros and cons of different types of approaches, and discuss some insights with respect to research trends. In addition, a lot of important sentiment analysis datasets are summarized in this survey." @default.
• W2938574033 created "2019-04-25" @default.
• W2938574033 creator A5018137331 @default.
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• W2938574033 creator A5064220732 @default.
• W2938574033 date "2019-07-01" @default.
• W2938574033 modified "2023-09-24" @default.
• W2938574033 title "Survey on Classic and Latest Textual Sentiment Analysis Articles and Techniques" @default.
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• W2938574033 doi "https://doi.org/10.1142/s0219622019300015" @default.
• W2938574033 hasPublicationYear "2019" @default.
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