188/4 E-Commerce Group
Institute of Software Technology and Interactive Systems
Vienna University of Technology
Favoritenstrasse 9-11/188, A-1040 Vienna, Austria

What Can We Learn From Review Data?

Authors: 
J. Neidhardt, N. Pobiedina, H. Werthner
Publisher: 
e-Review of Tourism Research
Proceedings: 
ENTER 2015: Volume 6
Pages: 
Year: 
2015
Type: 
Speech with CD or web proceedings
Hidden Keywords: 
Department Focus: 
Business Informatics
TU Focus: 
Information and Communication Technology
ISBN: 
ISSN: 1941-5842
Abstract: 
Online reviews of tourism services provide valuable resources of knowledge not only for travelers but also for companies. Tourism operators are more and more aware that user related data should be seen as an important asset. This work-in-progress analyzes free text reviews as well as numerical ratings of group tours with the aim to characterize their relations. This is done with the help of statistical models. On the one hand, these models comprise textual attributes and sentiment scores of the reviews, based on text mining techniques and sentiment analysis respectively. On the other hand, non-textual attributes such as meta data about the tours and user related factors are included. First results imply a very moderate relationship between sentiment scores and ratings; the non-textual attributes appear to have a higher impact.
Abstract German: