pearson correlation matrix

Understanding tourist behavior is a requirement for marketing planning for the supply of goods and services to satisfy tourists. Nowadays, many tourists decide to travel to any place by searching through internet explorers. The present study was conducted with the aim of analyzing the behavior of tourists in Iran based on data mining (search rate on Google Trend). The research is applied and has been done with a causal descriptive method. The method of collecting data is by searching keywords on Google. . To collect the keywords needed for the research, we had to turn to the experts and authorities on the field as well as the relevant scientific articles. The process of data collection is that a series of key words in tourism were selected and accordingly, it was determined how much people used these words in different places in Iran. Correlation matrix (covariance) model has been used for data analysis. In this research, the structural information of these keywords was obtained and edited based on the keywords related to tourism extracted from Google Trend by time series and with the help of Pearson correlation matrix. Nine keywords were selected for search, including hotel, entertainment, pilgrimage, tourism, nature, places of interest, archeology, travel and travel tour. The keywords are not searched at random, but they are related and correlated and stem from a structural thinking. The results of the data analysis have shown the type and intensity of connections between the words that had a communication structure. It was also found that the words pilgrimage, recreation, and archeology have less connection with other words.