Original scientific paper

Differences in travelers' perceptions of popular tourist destinations estimated by a LSTM neural network: A comparison between the UK and Germany

Kejo Starosta ; The Bucharest University of Economics Studies (ASE), Romania
Cristian Bogdan Onete ; The Bucharest University of Economics Studies (ASE), Bucharest, Romania
Sonia Budz ; The Bucharest University of Economics Studies (ASE), Bucharest, Romania
Michael Krutwig ; The Bucharest University of Economics Studies (ASE), Romania

Abstract

This study examines the differences and similarities in the perceptions of popular tourist destinations between the English and German media in an empirical and quantitative way. The perception of a tourist destination country is measured by the sentiment in the media in the tourists' countries of origin—either the UK or Germany. The study measures such perceptions with the help of a Long Short Term Memory (LSTM) artificial neural network that analyzes the perceptions in publicly available news streams in the UK and Germany. The results show that the online media indeed generates different perceptions for some of the popular travel destinations. An equally interesting finding is that there is, in general, a broad consensus between the sentiments in the British and German media. Businesses in the tourism and hospitality sectors, news providers, political actors, and policymakers can use the methodology to analyze the source of this information gap and the impact on their operations and policies.

Keywords

tourism; online media; sentiment analysis; machine learning; UK; Germany

Hrčak ID:

230638

URI

https://hrcak.srce.hr/230638

Publication date:

20.12.2019.

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