Identifying the destination image and its attributes: the case of central and eastern European cities

Marek Nowacki , Agnieszka Niezgoda

Abstract

The aim of the work is to identify the unique attributes of Central and Eastern European cities in the reviews posted on TripAdvisor. These attributes can determine the competitive advantage on the tourism market. The research data were downloaded from the English-language TripAdvisor website [https://www.tripadvisor.co.uk]. The reviews concerning tourist centres of selected cities (“Things to do in…” category) were collected. These concerned the areas where tourism is concentrated in the cities: historic centres, old towns or old market squares. The most popular tourism cities in Central and Eastern Europe were selected: Poznan, Wroclaw, Cracow, Warsaw, Prague, Bratislava and Vienna. A total of 28,794 reviews were downloaded. The most common words appearing in the reviews were counted using the text mining procedure. The analysis of frequency revealed 76 unique words. Then the correspondence analysis was performed. Among the examined cities, Bratislava has the largest number of unique attributes (words), and Prague the least. The similarities in terms of image attributes occur in Poznan, Wroclaw and Prague, and in the second group – Warsaw and Bratislava. Vienna and Krakow do not show any similarities towards the other cities.
Author Marek Nowacki
Marek Nowacki,,
-
, Agnieszka Niezgoda (WGM / KT)
Agnieszka Niezgoda,,
- Department of Tourism
Other language title versionsIdentyfikacja atrybutów wizerunku wybranych miast Europy środkowo-wschodniej
Journal seriesPrace Naukowe Uniwersytetu Ekonomicznego We Wrocławiu, ISSN 1899-3192, e-ISSN 2392-0041, [0324-8445], (N/A 20 pkt)
Issue year2019
Vol63
No8
Pages118-127
Publication size in sheets0.5
Keywords in PolishTripAdvisor, Text Mining, atrybuty, wizerunek, miasta
Keywords in EnglishTripAdvisor, text mining, attributes, image, cities
DOIDOI:10.15611/pn.2019.8.09
URL https://www.dbc.wroc.pl/dlibra/publication/142949/edition/74246
Languageen angielski
Score (nominal)20
Score sourcejournalList
ScoreMinisterial score = 20.0, 14-04-2020, ArticleFromJournal
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