Publisher
Springer Nature Switzerland
Reference68 articles.
1. Yan, H.-B., Li, Z.: Review of sentiment analysis: an emotional product development view. Front. Eng. Manag. 9(4), 592–609 (2022). https://doi.org/10.1007/s42524-022-0227-z
2. Alayba, A., Palade, V., England, M., Iqbal, R.: Arabic language sentiment analysis on health services. In: Proceedings of the 1st International Workshop on Arabic Script Analysis and Recognition (ASAR), Nancy, France, pp. 114–118. IEEE Computer Society (2017). https://doi.org/10.1109/ASAR.2017.8067771
3. Madni, H.A., et al.: Improving sentiment prediction of textual tweets using feature fusion and deep machine ensemble model. Electronics 12(6) (2023). https://doi.org/10.3390/electronics12061302
4. Radiuk, P., Pavlova, O., Hrypynska, N.: An ensemble machine learning approach for twitter sentiment analysis. In: Proceedings of the 6th International Conference on Computational Linguistics and Intelligent Systems, Gliwice, Poland (2022)
5. Kumar, S., Zymbler, M.: A machine learning approach to analyze customer satisfaction from airline tweets. J. Big Data 6(62) (2019). https://doi.org/10.1186/s40537-019-0224-1