Sentiment Analysis of Public Tendencies Towards the Israel-Palestine Conflict Using Bert Transformer on Platform X

This research addresses the analysis of public sentiment towards the Israel-Palestine conflict using the BERT Transformer model on the X platform. The main issues include the effectiveness of NLP methods for analyzing positive, negative, and neutral sentiments and the accuracy of these methods. The study implements a sentiment analysis algorithm using BERT, achieving an accuracy of 93% with precision, recall, and F1-Score of 0.95, 0.93, and 0.94, respectively. These results indicate high performance of the sentiment classification model. The conclusion highlights the model's satisfactory performance in predicting sentiment from tweets, although there is room for improvement, especially in handling neutral sentiments. This model can be confidently used for social media analysis, brand monitoring, and reputation management.