Sentiment Analysis of Israel-Palestine Conflict Comments Using Sentiment Intensity Analyzer and TextBlob

Abstract

Sentiment Analysis has kept its landmark in Natural Language Processing by analyzing the text to extract sentimental value. The result usually goes with positive, negative, or neutral sentiment with necessary data preprocessing, data processing, and encoding. This study explores sentiment analysis as it relates to statements made on the conflict between Israel and Palestine. It analyzes more modern options like Text Blob and Sentiment Intensity Analyzer in addition to more established ones like KNN and SVM. The study highlights the benefits of the latter two algorithms over more conventional methods and highlights their effectiveness and accuracy in sentiment analysis. We collected the dataset from Kaggle which obtains the comments taken from Reddit posts regarding the Israel-Palestine conflict and it has 4,36,425 threads in total. Inflight of this complex geopolitical problem, research into sentiment analysis algorithms and their applications advances our knowledge of public sentiment and geopolitical positions.