Can We Predict Your Sentiments by Listening to Your Peers?
Type:
Speech with proceedings
Proceedings:
ENTER Conference, Information and Communication Technologies in Tourism 2016
Publisher:
Springer International Publishing
Pages:
593 - 603
ISBN:
ISBN: 978-3-319-28230-5
Year:
2016
Abstract:
Web sources of tourism services provide valuable resources of knowledge not only for the travellers but also for the companies. Tourism operators are increasingly aware that user related data should be regarded as an important asset. In this paper, user activities and interactions in the tourism domain are analysed. In particular, the emotions of the users regarding their forthcoming trips are studied with the objective to characterize interdependencies between them. Social network analysis is applied to characterize the interactions between the users. To capture their emotions, text mining techniques and sentiment analysis are applied to construct a measure, which is based on free-text comments in a travel forum. The experimental outcome provides some evidence that social influence between the users in the network exists.
TU Focus:
Information and Communication Technology
Reference:
J. Neidhardt, N. Rümmele, H. Werthner:
"Can We Predict Your Sentiments by Listening to Your Peers?";
Vortrag: ENTER Conference 2016, Bilbao, Spain; 02.02.2016 - 05.02.2016; in: "ENTER Conference, Information and Communication Technologies in Tourism 2016", Springer International Publishing, Part V (2016), ISBN: 978-3-319-28230-5; S. 593 - 603.
Zusätzliche Informationen
Last changed:
25.07.2016 16:25:51
TU Id:
244730
Accepted:
Accepted
Invited:
Department Focus:
Business Informatics
Info Link:
https://publik.tuwien.ac.at/showentry.php?ID=244730&lang=1
Abstract German:
Web sources of tourism services provide valuable resources of knowledge not only for the travellers but also for the companies. Tourism operators are increasingly aware that user related data should be regarded as an important asset. In this paper, user activities and interactions in the tourism domain are analysed. In particular, the emotions of the users regarding their forthcoming trips are studied with the objective to characterize interdependencies between them. Social network analysis is applied to characterize the interactions between the users. To capture their emotions, text mining techniques and sentiment analysis are applied to construct a measure, which is based on free-text comments in a travel forum. The experimental outcome provides some evidence that social influence between the users in the network exists.