Forecasting the Tourists Demands Based on Google Trends Information Records by Machine Learning method (Case Study: Yazd tourists)

With the development of the tourism industry and the growth of related businesses, the need for up-to-date information in proper planning and accurate estimation of the number of tourists is essential for the efficient use of resources to develop infrastructure and increasing revenue. The existence of detailed plans will eventually lead to an increase in the satisfaction of incoming tourists. With the development of information search culture, tourists usually search for information about accommodation and tourism services in the destination through online resources before starting the trip. In the present study, using selected data related to user queries around the world in the Google search engine, about the tourism facilities and capabilities of Yazd, the number of future tourists in this city has been predicted. For this purpose, the research data consists of user search statistics, which were downloaded from the Google Trends system, and a prediction model was designed and validated using the machine learning method. After preparing and analyzing the data, it was found that the queries registered in Google Trends have a lot of power (more than 95%) in predicting the number of tourists in Yazd in the period from 2014 to 2019 in monthly periods.