The nature of electronic complaints about dark tourism destinations: a machine learning approach

Abstract

ABSTRACT Dark tourism studies are still underway and require further research, specifically related to understanding the stimuli for tourist complaints on dark tourism destinations. Thus, this study examines the electronic complaint attributes of visitors after visiting dark tourism destinations in Cambodia. Approximately 34,567 electronic complaint terms from 41 countries were manually retrieved and analyzed, using a natural language processing based Latent Dirichlet Allocation technique. The study revealed that complaints of visitors to dark tourism sites primarily pertain to eight topics: ‘human suffering affections,’ ‘historical site management,’ ‘political history,’ ‘environmental impact,’ ‘cultural awareness,’ ‘entrance fee policy,’ ‘accessibility,’ and ‘guide support.’ These insights are essential not only for tourism authorities to improve destination management, but also contribute to the literature on dark tourism.