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Shapley Additive Explanations for Text Classification and Sentiment Analysis of Internet Movie Database

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1716))

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Abstract

The application of Artificial Intelligence (AI) is increasing in areas like sentiment analysis and natural language processing (NLP). Automatic sentiment analysis provides a guide to capture the user emotions and classify the reviews into positive or negative. One of the challenges of using general lexicon analysis is its insensitivity to all domains. There arises a need for the interpretability of the output predicted from the AI sentiment analysis models. This paper developed a Shapley Additive Explanations for Text Classification (SHAP) based model to classify the user opinion texts into negative or positive labels. Our sentiment analysis model is evaluated on the Internet Movie Database (IMDB) datasets which have rich vocabulary and coherence of the textual data. Results showed that the model predicted 89% of the user reviews correctly. This model is very flexible for extending it to the unlabeled data.

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Acknowledgment

This paper is supported by the Ministry of Science and Technology, Taiwan. The Nos are MOST-107–2221-E-324 -018 -MY2 and MOST-109–2622-E-324-004, Taiwan.

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Authors and Affiliations

  1. Department of Information Management, Chaoyang University of Technology Taichung, Taiwan, Republic of China

    Christine Dewi, Bing-Jun Tsai, Rung-Ching Chen & Rung-Ching Chen

  2. Faculty of Information Technology, Satya Wacana Christian University, Salatiga, Indonesia

    Christine Dewi

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  1. Christine Dewi
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  2. Bing-Jun Tsai
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Correspondence to Rung-Ching Chen .

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Editors and Affiliations

  1. University of Newcastle Australia, Newcastle, NSW, Australia

    Edward Szczerbicki

  2. Wrocław University of Science and Technology, Wrocław, Poland

    Krystian Wojtkiewicz

  3. International University - VNU-HCM, Ho Chi Minh City, Vietnam

    Sinh Van Nguyen

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Marcin Pietranik

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Marek Krótkiewicz

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Dewi, C., Tsai, BJ., Chen, RC. (2022). Shapley Additive Explanations for Text Classification and Sentiment Analysis of Internet Movie Database. In: Szczerbicki, E., Wojtkiewicz, K., Nguyen, S.V., Pietranik, M., Krótkiewicz, M. (eds) Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2022. Communications in Computer and Information Science, vol 1716. Springer, Singapore. https://doi.org/10.1007/978-981-19-8234-7_6

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  • DOI: https://doi.org/10.1007/978-981-19-8234-7_6

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