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Tourism analytics with massive user-generated content: A case study of Barcelona
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“Studies, such as those of Marine-Roig and Clavé [47] and Xiang et al. [74], suggested that big data provides a huge amount of detail that contains deep-structure information on experiences, feelings, interests and opinions.”
From A Big Data Analytics Method for Tourist Behaviour Analysis (2017) · cites this paper as [47]
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Metadata
- Authors
- Marine-Roig, E., & Anton Clavé, S.
- ORCID
- Marine-Roig, Estela
- Venue
- Journal of Destination Marketing & Management
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 4
- Issue
- 3
- Pages
- 162-172
- ISSN
- 2212-571X (ISSN-L)
- OpenAlex
- W1609508549
- Cited by
- 356
- References
- 42
- Citations by year
- 2026: 28 · 2025: 18 · 2024: 35 · 2023: 34 · 2022: 43 · 2021: 40 · 2020: 42 · 2019: 40 · 2018: 33 · 2017: 24 · 2016: 17 · 2015: 2
- FWCI
- 84.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Destination Marketing & Management (publishedVersion)
- Funders
- Spanish Ministry of Economy and Competitiveness (MOVETUR CSO2014-51785-R)
- Topics
- Social Sciences › Business, Management and Accounting › Tourism, Leisure and Hospitality Management › Diverse Aspects of Tourism Research
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Business, Innovation, and Economy
- Keywords
- tourism analytics, user-generated content, online travel reviews, social media, big data analytics, smart cities, destination image, destination management, business intelligence, destination branding, destination positioning, travel blogs, Barcelona
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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