Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5252
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLeal,Fen
dc.contributor.authorDias,JMen
dc.contributor.authorBenedita Malheiroen
dc.contributor.authorBurguillo,JCen
dc.date.accessioned2018-01-02T15:44:11Z-
dc.date.available2018-01-02T15:44:11Z-
dc.date.issued2016en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/5252-
dc.identifier.urihttp://dx.doi.org/10.1145/2948992.2949008en
dc.description.abstractThe tourist behaviour has changed significantly over the last decades due to technological advancement (e.g., ubiquitous access to the Web) and Web 2.0 approaches (e.g., Crowdsourcing). Tourism Crowdsourcing includes experience sharing in the form of ratings and reviews (evaluation-based), pages (wiki-based), likes, posts, images or videos (social-network-based). The main contribution of this paper is a tourist-centred off-line and on-line analysis, using hotel ratings and reviews, to discover and present relevant trends and patterns to tourists and businesses. On the one hand, online, we provide a list of the top ten hotels, according to the user query, ordered by the overall rating, price and the ratio between the positive and negative Word Clouds reviews. On the other hand, off-line, we apply Multiple Linear Regression to identify the most relevant ratings that influence the hotel overall rating, and generate hotel clusters based on these ratings. © 2016 ACM.en
dc.languageengen
dc.relation5855en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.titleAnalysis and Visualisation of Crowd-sourced Tourism Dataen
dc.typeconferenceObjecten
dc.typePublicationen
Appears in Collections:CRAS - Articles in International Conferences

Files in This Item:
File Description SizeFormat 
P-00K-NJT.pdf592.58 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.