论文标题
使用机器学习对以色列的政治推文的情感分析
Sentiment Analysis of Political Tweets for Israel using Machine Learning
论文作者
论文摘要
情感分析是计算机科学领域的重要研究主题。随着信息技术和社交网络的加速发展，在Web应用程序或Twitter等社交媒体平台上生成了大量与评论文本有关的数据。因此，人们积极开始扩大一般信息和与政治观点有关的信息，这成为分析公共反应的重要原因。大多数研究人员使用社交媒体的细节或内容来分析和预测有关政治事件的公众舆论。这项研究提出了一项使用以色列政治Twitter数据的分析研究，以解释对巴勒斯坦 - 以色列冲突的公众舆论。使用机器学习算法（如支持向量分类器（SVC），决策树（DT）和Naive Bayes（NB））分析了种族群体和舆论领袖的态度。最后，基于不同模型的实验结果进行比较分析。
Sentiment Analysis is a vital research topic in the field of Computer Science. With the accelerated development of Information Technology and social networks, a massive amount of data related to comment texts has been generated on web applications or social media platforms like Twitter. Due to this, people have actively started proliferating general information and the information related to political opinions, which becomes an important reason for analyzing public reactions. Most researchers have used social media specifics or contents to analyze and predict public opinion concerning political events. This research proposes an analytical study using Israeli political Twitter data to interpret public opinion towards the Palestinian-Israeli conflict. The attitudes of ethnic groups and opinion leaders in the form of tweets are analyzed using Machine Learning algorithms like Support Vector Classifier (SVC), Decision Tree (DT), and Naive Bayes (NB). Finally, a comparative analysis is done based on experimental results from different models.
