Abstract
Authenticity perceptions are subjectively driven and rely on social constructions making the concept hard to be defined. The current study is following a big data approach to capture perceptions and beliefs concerning the authenticity of ethnic restaurants and also when online positive reviews are given about authenticity under the influence of a visit to the country of origin. The key idea of our method relies on the analysis of a 3-step characterization of a big data repository extracted from TripAdvisor. Step 0 concerns reviews made for Italian restaurants before consumers visit Italy, step 1 concerns the reviews made while consumers were in Italy and step 2 concerns reviews made after they visited Italy. This characterization exploits both sentiment analysis and graph data models. Our findings propose a depiction of authenticity for ethnic restaurants via e-word of mouth. With a big data analysis on TripAdvisor, we provided an analysis on both ratings and comments which showed the impact of authenticity. As such, consumers, after visiting the country of origin, were more critical while they provided lower ratings and they were also focusing more on authentic atmosphere and service, showing evolution of their online reviews.
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Chatzopoulou, E., Travers, N. (2022). Authenticity Goes Digital: A Big Data Analysis of the Influence of the Country of Origin and Authenticity Perceptions on TripAdvisor Ethnic Restaurant Reviews. In: Pantoja, F., Wu, S. (eds) From Micro to Macro: Dealing with Uncertainties in the Global Marketplace. AMSAC 2020. Developments in Marketing Science: Proceedings of the Academy of Marketing Science. Springer, Cham. https://doi.org/10.1007/978-3-030-89883-0_2
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