The Use of a Sentiment Analysis/Opinion Mining Technique with Machine Learning Algorithms to Develop Twitter-Related Themes in the Saudi Arabian Context

Abstract

Twitter is the most popular and valuable resource for sentiment analysis. This observation holds because the platform ensures that individuals express their thoughts and ideas regarding various topics, especially about social life. With users restricted to 140 characters or less, Twitter has evolved as one of the most dominant social networking websites in the world. This research has two main aspects. The first objective is to demonstrate the implementation of sentiment analyzer for Tweeter’s comments, which is considered as one of the most critical and freely big data sources. We analyzed Arabic text using Saudi dialect tweets to get the sentiments around a particular topic in Saudi Arabia. After Indeed, we evaluated the algorithms implemented by using confusion matrix. The second objective was to examine the challenges and complexities in Arabic text, especially those that make the Arabic sentiment analysis more complex than other languages.