Data · dataset · 2025
A Dataset of TripAdvisor Guest Reviews for Major Hotels in Salalah, Oman
Listed in Teesside University Research Data Repository
This dataset contains TripAdvisor guest reviews for major hotels in Salalah, Oman, collected through web scraping.
Description
It provides insights into guest satisfaction, sentiment, and ratings, making it a valuable resource for marketing, hospitality and tourism research, sentiment analysis, and tourism marketing studies. 𝐇𝐨𝐭𝐞𝐥𝐬 𝐈𝐧𝐜𝐥𝐮𝐝𝐞𝐝 𝐢𝐧 𝐭𝐡𝐞 𝐃𝐚𝐭𝐚𝐬𝐞𝐭 The dataset features guest reviews from the following hotels in Salalah: • Al Baleed Resort Salalah by Anantara • Belad Bont Resort • Crowne Plaza Resort Salalah • Fanar Hotel and Residences • Hilton Salalah Resort • Juweira Boutique Hotel • Millennium Resort Salalah • Salalah Gardens Hotel • Salalah Rotana Resort 𝐓𝐢𝐦𝐞 𝐂𝐨𝐯𝐞𝐫𝐚𝐠𝐞 The dataset captures all available guest reviews from the beginning of each hotel's presence on TripAdvisor up until February 2025. 𝐑𝐞𝐥𝐞𝐯𝐚𝐧𝐜𝐞 𝐭𝐨 𝐊𝐡𝐚𝐫𝐞𝐞𝐟 𝐓𝐨𝐮𝐫𝐢𝐬𝐦 𝐎𝐦𝐚𝐧 𝐕𝐢𝐬𝐢𝐨𝐧 2040 This dataset is particularly beneficial for the following government agencies: • Ministry of Heritage and Tourism - Oman • Oman Chamber of Commerce & Industry (OCCI) • Dhofar Municipality and Dhofar Tourism Department • National Centre for Statistics and Information (NCSI) • Oman Vision 2040 Implementation Follow-up Unit • Ministry of Commerce, Industry, and Investment Promotion • Oman Tourism Development Company (OMRAN) • Ministry of Transport, Communications, and Information Technology (MTCIT) • Dhofar Governorate Office • Ministry of Environment and Climate Affairs It also serves as a valuable resource for researchers, policymakers, and marketing, hospitality & tourism professionals to enhance Salalah’s tourism sector, improve guest satisfaction, and support Oman’s long-term vision for a thriving and sustainable tourism industry.
Salalah experiences a surge in visitors during the Khareef season (monsoon season), a critical period for the hospitality industry. This dataset can help analyze guest experiences, identify service gaps, and optimize offerings during this peak tourism period. Oman Vision 2040 Goals The dataset aligns with Oman’s Vision 2040, which prioritizes tourism sector growth, economic diversification, and enhanced customer experiences.
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By leveraging sentiment analysis and guest insights, policymakers and hotel managers can develop data-driven strategies to improve hospitality services, attract more visitors, and enhance Salalah’s reputation as a premier travel destination. Potential Use Cases Sentiment Analysis: Understanding guest satisfaction trends over time Tourism & Hospitality Research: Evaluating service quality and hotel performance across different years Marketing Insights: Identifying key drivers of positive and negative reviews for strategic decision-making Machine Learning & NLP: Training models for text classification, sentiment prediction, and recommendation systems
Links
Where it is published
- DOI doi.org/10.17632/dkfwj76kx6.3 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Economics & Finance · Hospitality management · Humanities · Medicine & Health · Natural language processing · Psychology & Behavioral Science · Social Science
- Inferred from text
- Text 75%
Related
- Possibly the same asA Dataset of TripAdvisor Guest Reviews for Major Hotels in Salalah, Oman
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/dkfwj76kx6.3 | 16 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:350402 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Hospitality Management'] |
| concepts[field].anzsrc:field:460208 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Natural Language Processing'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:text | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |