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On Students’ Sentiment Prediction Based on Deep Learning: Applied Information Literacy

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Abstract

The main purpose of this study is to understand the assessment of students’ sentiments on improving the role of library service quality after the pandemic and deduce the trends consistent with the new phase of technology. In this study, convolution bidirectional learners (CBLs) are employed for evaluating such as Convolution Bidirectional Long Short-Term Memory (CBLSTM), Gated Recurrent Unit (CBGRU), Simple Recurrent Neural Network (CBSRNN), Combination of Convolutional Bidirectional LSTM+GRU (CBLSTMGRU), SimpleRNN+LSTM (CBSLSTM), SimpleRNN+GRU (CBSGRU), Attention, and Transformer TFBERT model. The results show that CBSLSTM (94.82% accuracy) and CBLSTMGRU (94.78% accuracy) surpassed the other models in predicting Vietnamese students’ sentiments.

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Acknowledgements

The authors acknowledge the reviewer’s comments that contribute to improving the paper’s quality and confirm that the data used in this paper is under the consent of agreement.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, FernUniversität in Hagen, Universitätsstraße 47, Hagen, 58097, Hagen, Germany

    Nguyen Minh Tuan

  2. Department of Information Technology and Management, King Mongkut’s University of Technology North Bangkok, Pracharat, Bangsue, 10800, Bangkok, Thailand

    Phayung Meesad

  3. Faculty of Engineering Technology, Tien Giang University, Ap Bac, My Tho, 860000, Tien Giang, Viet Nam

    Duong Van Hieu

  4. Software Development Centre, University of Danang, Le Duan, Hai Chau, 50000, Danang, Viet Nam

    Nguyen Ha Huy Cuong

  5. Department of Information Technology, King Mongkut’s University of Technology North Bangkok, Pracharat, Bangsue, 10800, Bangkok, Thailand

    Maleerat Maliyaem

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  1. Nguyen Minh Tuan
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  2. Phayung Meesad
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  3. Duong Van Hieu
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  4. Nguyen Ha Huy Cuong
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Contributions

Nguyen Minh Tuan: Conceptualization, data curation, investigation, methodology, software, visualization, writing-original draft and writing-review and editing, validation, visualization, writing-original draft and writing-review and editing. Phayung Meesad: Conceptualization, formal analysis, methodology, resources, supervision, validation, visualization, and writing review and editing. Duong Van Hieu: methodology, resources, supervision, validation, visualization, and writing review and editing. Nguyen Ha Huy Cuong: methodology, resources, supervision, validation, visualization, and writing review and editing. Maleerat Maliyaem: methodology, resources, supervision, validation, visualization, and writing review and editing.

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Correspondence to Nguyen Minh Tuan or Phayung Meesad.

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Tuan, N.M., Meesad, P., Hieu, D.V. et al. On Students’ Sentiment Prediction Based on Deep Learning: Applied Information Literacy. SN COMPUT. SCI. 5, 928 (2024). https://doi.org/10.1007/s42979-024-03281-7

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