Measuring Destination Image Using AI and Big Data: Kastoria’s Image on TripAdvisor

Abstract

In recent years, the growing number of Online Travel Review (OTR) platforms and advances in social media and search engine technologies have led to a new way of accessing information for tourists, placing projected Tourist Destination Image (TDI) and electronic Word of Mouth (eWoM) at the heart of travel decision-making. This research introduces a big data-driven approach to analyzing and measuring the perceived and conveyed TDI in OTRs concerning the reflected perceptive, spatial, and affective dimensions of search results. To test this approach, a massive metadata analysis of search engine was conducted on approximately 2700 reviews from TripAdvisor users for the category “Attractions” of the city of Kastoria, Greece. Using artificial intelligence, an analysis of the photos accompanying user comments on TripAdvisor was performed. Based on the results, we created five themes for the image narratives, depending on the focus of interest (monument, activity, self, other person, and unknown) in which the content was categorized. The results obtained allow us to extract information that can be used in business intelligence applications.

Keywords

• destination image
• data mining
• image recognition
• user-generated content
• projected image
• perceived image