International Journal of Geo-Information Article Applying GIS and Text Mining Methods to Twitter Data to Explore the Spatiotemporal Patterns of Topics of Interest in Kuwait Muhammad G. Almatar 1,* , Huda S. Alazmi 2,† , Liuqing Li 3,†,‡ and Edward A. Fox 3 1 Department of Geography, Kuwait University, Safat 13060, Kuwait 2 Curriculum & Instruction Department, Kuwait University, Kuwait 71423, Kuwait;
[email protected] 3 Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA;
[email protected] (L.L.);
[email protected] (E.A.F.) * Correspondence:
[email protected]; Tel.: +965-909-12345 † These authors contributed equally to this work. ‡ The work was done when Liuqing Li was a PhD student at Virginia Tech. Received: 16 September 2020; Accepted: 17 November 2020; Published: 25 November 2020 Abstract: Researchers have developed various approaches for exploring the spatial information, temporal patterns, and Twitter content in topics of interest in order to generate a better understanding of human behavior; however, few investigations have integrated these three dimensions simultaneously. This study analyzes the content of tweets in order to conduct a spatiotemporal exploration of the main topics of interest in Kuwait in order to provide a deeper understanding of the topics people think about, when they think about them, and where they tweet about them. To this end, we collect, process, and analyze tweets from nearly 120 areas in Kuwait over a 10-month period. The study’s results indicate that religion, emotions, education, and public policy are the most popular topics of interest in Kuwait. Regarding the spatiotemporal analysis, people post more tweets regarding religion on Fridays, a holy day for Muslims in Kuwait.