Mohammed Yaqot and Abdullatif Albaseer
Nowadays, most people disclose their opinions and decisions toward anything by writing tweets. Analyzing and clustering those opinions known as data mining. Exploiting the integration between the existing technologies, particularly web and geographic information system (GIS), would enable determining people’s location and analyzing their reactions to different aspects of life using the smart engine (sentiment analysis). Marketing sector, for instance, is progressively seeking to generate useful reports that help in analyzing big data by its location to maximize sales and adaptively take corrective actions in the shortest time with least cost. In this paper, a web application has been introduced using nodeJS, JavaScript, MongoDB online database, Twitter APIs, and Google map APIs (including; Geocoding, Reverse Geocoding, and Google map markers). It was found that those tools could integrate, manage, and visualize spatial data with respect to geo-located tweets and its sentiment. Consequently, this application offers convenient, flexible, honest, selective, tailored to different needs, immediate, unrestricted and updated information that help the user to extract features from a large data set of tweets.
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