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1. Nguyen, K.V., Nguyen, V.D., Nguyen, P., Truong, T., Nguyen, N.L.T.: UIT-VSFC: Viet-
namese -ternational
Conference on Knowledge and Systems Engineering (KSE). pp. 19 24. IEEE, Ho Chi
Minh City, Vietnam (2018).
2. Cummins, S., Burd, L., Hatch, A.: Using Feedback Tags and Sentiment Analysis to Gener-
ate Sharable Learning Resources Investigating Automated Sentiment Analysis of Feedback
Tags in a Programming Course. In: 2010 10th IEEE International Conference on Ad-
vanced Learning Technologies. pp. 653-657. IEEE, Sousse, Tunisia (2010).
3. Menaha, R., Dhanaranjani, R., Rajalakshmi, T., Yogarubini, R.: Student Feedback Mining
System Using Sentiment Analysis. In: International Journal of Computer Applications
Technology and Research. IJCATR, vol. 6, no. 1, pp. 51-55 (2017).
4. Abdelrazeq, A., Janssen, D., Tummel, C., Jeschke, S., Richert, A.: Sentiment Analysis of
Social Media for Evaluating Universities. In: Proceeding of Second International Confer-
ence on Digital Information Processing, Data Mining, and Wireless Communications. pp.
49-62. (DIPDMWC2015), Dubai, UAE (2015).
5. Baradwaj, B.K., Pal, S.: . In:
October 2011 International Journal of Advanced Computer Science and Applications.
IJACSA, vol. 2, no. 6, pp. 63-69 (2011).
6. Mendez, J.T., Lobel, H., Parra, D., Herrera, J.C.: Using Twitter to Infer User Satisfaction
With Public Transport: The Case of Santiago, Chile. In: IEEE Access. vol. 7, pp. 60255-
60263, IEEE (2019).
7. Trinh, S., Nguyen, L., Vo, M.: Combining Lexicon-Based and Learning-Based Methods
for Sentiment Analysis for Product Reviews in Vietnamese Language. In: Lee, R. (eds)
Computer and Information Science. ICIS 2017. Studies in Computational Intelligence, vol.
719, pp. 57-75. Springer, Cham (2018).
8. Nguyen, H.N., Le, T.V., Le, H.S., Pham, T. V.: Domain Specific Sentiment Dictionary for
Opinion Mining of Vietnamese Text. In: Murty, M.N., He, X., Chillarige, R.R., Weng, P.
(eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2014. Lecture Notes in
Computer Science (), vol. 8875. Springer, Cham (2014).
9. Bang, T.S., Haruechaiyasak, C., Sornlertlamvanich, V.: Vietnamese Sentiment Analysis
Based on Term Feature Selection Approach, In: 10th International Conference on
Knowledge Information and Creativity Support Systems (KICSS), pp. 196-204 (2015).
10. Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: Pre-training of Deep Bidirectional
Transformers for Language Understanding. In: Proceedings of the 2019 Conference of the
North American Chapter of the Association for Computational Linguistics: Human Lan-
guage Technologies, vol. 1, pp. 4171-4186, Minneapolis, Minnesota (2019).

CITA 2023 ISBN: 978-604-80-8083-9