Targeting tourist behavior at global events could be one of the interesting topics for business houses. Location Based Analytical - Business Intelligent (LBA-BIntelligent) frameworks predict targeted tourist behavior at global events. The organizing countries create new businesses and gain a competitive advantage from tourists. This framework streamlines marketing to the right people at the right time. This study focuses on implementing bagging and boosting ensemble approaches. These classifiers have been evaluated on various parameters such as accuracy, precision, recall, F-score, Kappa score, and ROC-AUC score. The classification results show that the bagging approach gives better results through all the evaluation metrics.
TopTwitter has been a popular platform for people to share their stories. Each day twitter has a new topic trending with hashtags of on-going event, some of the trending hashtags were #GlobalWarming, #WorldCup, #pandemic. Individuals tend to share their reactions during storms (Dunkel et al., 2019), earthquake (Dragovic et al., 2019), geography or weather (André et al., 2015; Denissen, Butalid, Penke, & Van Aken, 2008; Denissen, Butalid, Penke, & Van Aken, 2008; Howarth & Hoffman, 1984; Shah, Martin, Coiera, Mandl, & Dunn, 2019). This popular social media is also used for analysing characteristics of tweets such as spatial and temporal factors (Baylis, 2015; Klimstra et al., 2011), variation of tweets at different times of the day, day of the week (Egloff et al., 1995; Golder & Macy, 2011).