Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/4049
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dc.contributor.authorLeal, Fátima-
dc.contributor.authorMalheiro, Benedita-
dc.contributor.authorVeloso, Bruno-
dc.contributor.authorBurguillo, Juan Carlos-
dc.date.accessioned2022-04-28T10:56:39Z-
dc.date.available2022-04-28T10:56:39Z-
dc.date.issued2020-07-13-
dc.identifier.citationLeal, F., Malheiro, B., Veloso, B., & Burguillo, J. C. (2020). Responsible processing of crowdsourced tourism data. Journal of Sustainable Tourism, 29(5), 774-794. https://doi.org/10.1080/09669582.2020.1778011. Repositório Institucional UPT. http://hdl.handle.net/11328/4049pt_PT
dc.identifier.issn0966-9582 (Print)-
dc.identifier.issn1747-7646 (Electronic)-
dc.identifier.urihttp://hdl.handle.net/11328/4049-
dc.description.abstractOnline tourism crowdsourcing platforms, such as AirBnB, Expedia or TripAdvisor, rely on the continuous data sharing by tourists and businesses to provide free or paid value-added services. When adequately processed, these data streams can be used to explain and support businesses in the early identification of trends as well as prospective tourists in obtaining tailored recommendations, increasing the confidence in the platform and empowering further end-users. However, existing platforms still do not embrace the desired accountability, responsibility and transparency (ART) design principles, underlying to the concept of sustainable tourism. The objective of this work is to study this problem, identify the most promising techniques which follow these principles and design a novel ART-compliant processing pipeline. To this end, this work surveys: (i) real-time data stream mining techniques for recommendation and trend identification; (ii) trust and reputation (T&R) modelling of data contributors; (iii) chained-based storage of trust models as smart contracts for traceability and authenticity; and (iv) trust- and reputation-based explanations for a transparent and satisfying user experience. The proposed pipeline redesign has implications both to digital and to sustainable tourism since it advances the current processing of tourism crowdsourcing platforms and impacts on the three pillars of sustainable tourism.pt_PT
dc.language.isoengpt_PT
dc.publisherTaylor & Francis Onlinept_PT
dc.rightsrestrictedAccesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAccountabilitypt_PT
dc.subjectAuthenticitypt_PT
dc.subjectCrowdsourcingpt_PT
dc.subjectData stream miningpt_PT
dc.subjectDigital tourismpt_PT
dc.subjectExplainabilitypt_PT
dc.subjectRecommendationspt_PT
dc.subjectResponsibilitypt_PT
dc.subjectTraceabilitypt_PT
dc.subjectSustainabilitypt_PT
dc.subjectTransparencypt_PT
dc.subjectTrendspt_PT
dc.titleResponsible processing of crowdsourced tourism datapt_PT
dc.typearticlept_PT
dc.relation.publisherversionhttps://www.tandfonline.com/doi/full/10.1080/09669582.2020.1778011pt_PT
dc.peerreviewedyespt_PT
degois.publication.firstPage774pt_PT
degois.publication.lastPage794pt_PT
degois.publication.volume29pt_PT
degois.publication.issue5pt_PT
degois.publication.titleJournal of Sustainable Tourismpt_PT
dc.identifier.doihttps://doi.org/10.1080/09669582.2020.1778011pt_PT
Appears in Collections:REMIT – Artigos em Revistas Internacionais / Papers in International Journals

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