Agnieszka Niezgoda

Abstract

The article aims to identify memorable gastronomic experiences reported online and verify their relationships with the type of cuisine served and restaurant location. This study used text mining, LDA, Pearson’s chi-squaredtest and sentiment analysis. All 48,378 English reviews posted by TripAdvisor users concerning 155 restaurants in Krakow were scraped. Eight features that characterise MGEs were identified (service/staff, atmosphere,cuisine/food (taste), drinks, local specialities, location/setting, price & value and table booking). There are statistically significant differences in the frequency of the topic experiences depending on the location of restaurants in the city.

Keywords: food tourism, culinary experiences, Krakow, restaurant management, Latent Dirichlet Allocation, sentiment analysis

Marek Nowacki [marek.nowacki@poznan.merito.pl], WSB Merito University in Poznań Powstańców Wielkopolskich 5, 61-895 Poznań: Poland
Andrzej Stasiak [andrzej.stasiak@geo.uni.lodz.pl], Institute of Urban Geography, Tourism Studies, and Geoinformation, Faculty of Geographical Sciences University of Lodz, Kopcińskiego 31, 90-142 Łódź: Poland
Agnieszka Niezgoda [agnieszka.niezgoda@ue.poznan.pl], Department of International Economics Poznań University of Economics and Business Aleja Niepodległości 10, 61-875 Poznań: Poland