Univrsity Of Tehran Press Journal of Information Technology Management 2980-7972 18 3 2026 07 01 Twitt Ray: Sentiment Visualization of Arabic Tweets 155 180 108009 10.22059/jitm.2026.108009 EN Nadia Al-Ghreimil Assistant Prof., Department of Information Technology, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. Manal Alhassoun Data Scientist and Research Associate, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia. Nora Al-Twairesh Associate Professor, Department of Information Technology, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. Duaa AlSaeed Prof., College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. Journal Article 2026 07 20 Sentiment Analysis of Twitter offers valuable insight into public sentiment. However, humans absorb most information through visual perception. Therefore, visual representation of data enables them to comprehend data more quickly and effectively than in text form. Unfortunately, the majority of ex-isting work mainly focuses on sentiment analysis and pays less attention to sentiment visualization; this potentially reduces the real value of sentiment analysis results. In this paper, we present an easy-to-use sentiment visualization tool for Arabic tweets called Twitt Ray. The goal of Twitt Ray is to serve anyone, from individuals to companies and social scientists, who are interested in knowing, analyzing, and visualizing the current sentiments that people express on Twitter. Moreover, Twitt Ray provides seven different visual representations of sentimentally analyzed data to achieve a better understanding of different aspects of the data. Also, a usability study was performed to evaluate the usability of the tool for end users. https://jitm.ut.ac.ir/article_108009_1a18be5fc0a00b43a51b9fa3d99c401c.pdf