Exploring consumer behavior through user-generated content on TripAdvisor. The case of Holguin destination

Abstract

The present study explores consumer behavior of tourists through user-generated content by presenting a method that utilizes online reviews and text processing techniques in analyzing behavior patterns. The current study examined 7,856 travel reviews from TripAdvisor written by international tourists visiting Holguin (Cuba) destination. This method includes the overall process of converting raw data into useful information, which comprises selection, pre-processing, data mining and interpretation. Data are collected from online review platforms rather than from traditional databases, and the first step is data crawling. Then, unstructured review content is transformed into suitable formats for analysis. The final step is exploratory data analysis, which includes both data mining and interpretation. Findings show that the cognitive dimension of the experience predominates in consumer's behavior. The study identifies topics that could be used by destination management organizations to promote this destination and highlights the advantages of applying a data science approach.