NORMA eResearch @NCI Library

Responsible processing of crowdsourced tourism data

Leal, Fátima, Malheiro, Benedita, Veloso, Bruno and Burguillo, Juan Carlos (2020) Responsible processing of crowdsourced tourism data. Journal of Sustainable Tourism. pp. 774-794. ISSN 1747-7646

Full text not available from this repository.
Official URL: https://doi.org/10.1080/09669582.2020.1778011

Abstract

Online 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.

Item Type: Article
Uncontrolled Keywords: Accountability; authenticity; crowdsourcing; data stream mining; digital tourism; explainability; recommendations; responsibility; sustainability; traceability; transparency; trends
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
H Social Sciences > HF Commerce > Business Ethics
H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Tourism Industry
Divisions: School of Computing > Staff Research and Publications
Depositing User: Tamara Malone
Date Deposited: 09 Jul 2025 14:35
Last Modified: 09 Jul 2025 14:35
URI: https://norma.ncirl.ie/id/eprint/8073

Actions (login required)

View Item View Item