How are tourism destinations perceived on social media? A recent study by Ilona Pezenka from the Marketing & Sales Management Study Programs, conducted in collaboration with international research partners, demonstrates how the image of travel destinations can be automatically analyzed and compared using AI and text mining.
The image of a tourism destination significantly influences how attractive it appears to travelers. For Destination Management Organizations (DMOs), it is therefore crucial to understand which characteristics visitors associate with a destination. The recent study “Microblog data: Measuring tourism destination image using importance-performance analysis”, published by Ilona Pezenka together with Christian Weismayer (Modul University Vienna) and Melise de Lima Pereira (Federal University of Paraná, Curitiba, Brazil) in the Sage Journal Tourism and Hospitality Research, demonstrates how these perceptions can be automatically captured using social media data.
New method makes destination image visible on social media
The study focuses on an approach to analyzing posts on Platform X. The researchers used four Brazilian coastal destinations as case studies and combined text mining techniques with artificial intelligence methods.
First, a classification algorithm determines the significance of various forms of tourism. This is based on the 14 tourism categories defined by the United Nations World Tourism Organization (UN Tourism). Subsequently, a multilingual natural language processing (NLP) model assesses the sentiment in the posts and analyzes how individual aspects of the destinations are perceived. The results are then consolidated into so-called importance-performance grids, which clearly illustrate the perceived destination image.
Automated AI analysis as the basis for systematic comparison
This approach enables the fully automated analysis of large volumes of user-generated content. At the same time, it lays the groundwork for a systematic comparison of different destinations. This provides tourism organizations with a tool that supports data-driven decision-making in destination development and marketing.
The study also highlights the potential of modern AI methods for tourism research: travelers’ perceptions can not only be captured more quickly but also analyzed at a level of detail that was previously difficult to achieve.