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Articles related to psychological literature behind the semantics work. References Aguinta, D. J., Adikara, P. P., & Wihandika, R. C. (2020). Sentiment analysis of mass rapid transit jakarta using naïve bayes classifier and rule-based opinion target detection on Twitter. Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology. https://doi.org/10.1145/3427423.3427437 Chen, Z., Cao, Y., Yao, H., Lu, X., Peng, X., Mei, H., & Liu, X. (2021). Emoji-powered Sentiment and Emotion Detection from Software Developers’ Communication Data. ACM Transactions on Software Engineering and Methodology, 30(2), 1–48. https://doi.org/10.1145/3424308 Costa-jussà, M. R., España-Bonet, C., Fung, P., & Smith, N. A. (2020). Multilingual and Interlingual Semantic Representations for Natural Language Processing: A Brief Introduction. Computational Linguistics, 46(2), 249–255. https://doi.org/10.1162/coli_a_00373 de Barros, T. M., Pedrini, H., & Dias, Z. (2021). Leveraging emoji to improve sentiment classification of tweets. Proceedings of the 36th Annual ACM Symposium on Applied Computing. https://doi.org/10.1145/3412841.3441960 de Barros, T. M., Pedrini, H., & Dias, Z. (2021). Leveraging emoji to improve sentiment classification of tweets. Proceedings of the 36th Annual ACM Symposium on Applied Computing. https://doi.org/10.1145/3412841.3441960 Gongda, Q., Guixin, Z., Hui, S., & Liqiong, D. (2020). A comprehensive sentiment analysis method based on Sentiment Multi-label and Probabilistic Hesitant Fuzzy Decision-making. Proceedings of the 2020 4th International Conference on Electronic Information Technology and Computer Engineering. https://doi.org/10.1145/3443467.3443751 Guangce, R., & Lei, X. (2021). Knowledge Discovery of News Text Based on Artificial Intelligence. ACM Transactions on Asian and Low-Resource Language Information Processing, 20(1), 1–18. https://doi.org/10.1145/3418062 Huang, F., Wei, K., Weng, J., & Li, Z. (2020). Attention-Based Modality-Gated Networks for Image-Text Sentiment Analysis. ACM Transactions on Multimedia Computing, Communications, and Applications, 16(3), 1–19. https://doi.org/10.1145/3388861 Ikram, A., & Castle, B. (2020). Automated Essay Scoring (AES); A Semantic Analysis Inspired Machine Learning Approach. 2020 12th International Conference on Education Technology and Computers. https://doi.org/10.1145/3436756.3437036 Lee, R., & Lyu, J. (2020). Sentiment Analysis of Product Reviews Based on JST Model. Proceedings of the 4th International Conference on Computer Science and Application Engineering. https://doi.org/10.1145/3424978.3425097 Liesting, T., Frasincar, F., & Truşcă, M. M. (2021). Data augmentation in a hybrid approach for aspect-based sentiment analysis. Proceedings of the 36th Annual ACM Symposium on Applied Computing. https://doi.org/10.1145/3412841.3441958 Pazmiño, R., Badillo, F., González, M. C., & García-Peñalvo, F. J. (2020). Ecuadorian Higher Education in COVID-19: A Sentiment Analysis. Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality. https://doi.org/10.1145/3434780.3436679 Rocha, R. S., Saraiva, L. A., de Castro, A. F., & de Alencar Silva, P. (2020). Sentiment analysis of Twitter data about blockchain technology. Proceedings of the 10th Euro-American Conference on Telematics and Information Systems. https://doi.org/10.1145/3401895.3401913 Samtani, S., Kantarcioglu, M., & Chen, H. (2021). A Multi-Disciplinary Perspective for Conducting Artificial Intelligence-enabled Privacy Analytics. ACM Transactions on Management Information Systems, 12(1), 1–18. https://doi.org/10.1145/3447507 Wijayanti, R., & Arisal, A. (2021). Automatic Indonesian Sentiment Lexicon Curation with Sentiment Valence Tuning for Social Media Sentiment Analysis. ACM Transactions on Asian and Low-Resource Language Information Processing, 20(1), 1–16. https://doi.org/10.1145/3425632