Record: oai:ARNO:641696

AuteurB. Dumas
TitelAre satisfaction patterns better explained by using classic industry characteristics? : a different view on sentiment and topic analysis in hotel reviews
BegeleiderK. Valogianni
FaculteitFaculteit Economie en Bedrijfskunde
OpleidingFEB MSc Business Administration
SamenvattingData of all sorts is expanding rapidly. Business intelligence departments are making more and more use of big data to make strategic business decisions. A specific form of this data is User Generated Content (UGC), such as consumer generated online product reviews. For the hotel industry specifically, consumer reviews contain a lot of useful information about consumer preferences that could help to better predict demand and to allocate resources more efficiently. The hotel industry must deal with seasonality and fluctuating periods of demand. Consequently, over- or under-utilization of hotel resources can occur, which could impact guest satisfaction. Therefore, it is important to know which specific factors are most important for consumers in different demand periods, and how this varies between different hotel sizes and hotel segments. This paper uses text analytics to analyse hotel reviews on a large scale, and takes the abovementioned industry variables in account. The results of the analysis show that indeed the sentiment in reviews varies in different demand periods, high and low season to be specific. Also, this effect is being influenced by hotel size and segment. Furthermore, this paper shows that the distribution of topics in reviews and its influence on the sentiment is different in high and low season and that this effect is influenced by hotel size and segment as well. Unlike previous research, this paper shows that valuable insights from consumer reviews, such as the sentiment and the distribution of topics, differs significantly across several industry variables.
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