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Responsible processing of crowdsourced tourism data

2020-07Artigo científico Acesso restrito
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dc.contributor.authorLeal, Fátima
dc.contributor.authorMalheiro, Benedita
dc.contributor.authorVeloso, Bruno
dc.contributor.authorBurguillo, Juan Carlos
dc.date.accessioned2020-07-28T08:45:26Z
dc.date.embargo2119
dc.date.issued2020-07
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.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1080/09669582.2020.1778011pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/16119
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor & Francispt_PT
dc.relation.publisherversionhttps://doi.org/10.1080/09669582.2020.1778011pt_PT
dc.subjectAccountability, responsibility and transparencypt_PT
dc.subjectAuthenticity and traceabilitypt_PT
dc.subjectCrowdsourcingpt_PT
dc.subjectRecommendationpt_PT
dc.subjectData stream miningpt_PT
dc.subjectExplainabilitypt_PT
dc.subjectDigital tourismpt_PT
dc.subjectSustainabilitypt_PT
dc.subjectTrendspt_PT
dc.titleResponsible processing of crowdsourced tourism datapt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage21pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleJournal of Sustainable Tourismpt_PT
person.familyNameLeal
person.familyNameBENEDITA CAMPOS NEVES MALHEIRO
person.givenNameFátima
person.givenNameMARIA
person.identifier.ciencia-id2211-3EC7-B4B6
person.identifier.ciencia-id7A15-08FC-4430
person.identifier.orcid0000-0003-4418-2590
person.identifier.orcid0000-0001-9083-4292
person.identifier.ridY-3460-2019
person.identifier.scopus-author-id57190765181
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication8e77ca2d-3cb2-4346-927b-a706a5580c9e
relation.isAuthorOfPublicationbabd4fda-654a-4b59-952d-6113eebbb308
relation.isAuthorOfPublication.latestForDiscoverybabd4fda-654a-4b59-952d-6113eebbb308

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