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August 6, 2025Advances in Hospitality and Tourism Research (AHTR)Open Access

Bibliometric Analysis of Publications on Recommender Systems in Tourism: Web of Science Case

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Authors

MÇMurat ÇuhadarSuleyman Demirel University

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Implication

Bibliometric analysis identifies trends and key contributors in recommender systems research in tourism, highlighting AI and ML's roles.

Key Points

  • MAIN FINDING: Research on recommender systems in tourism reveals significant contributions from Europe and Asia.
  • KEY EVIDENCE: With 495 publications, AI and ML are the dominant technological drivers in this field.
  • APPROACH: Co-authorship and co-citation analyses highlight four main research clusters and interdisciplinary integrations.
  • SIGNIFICANCE: This mapping provides insights into research gaps and future directions for academics and policymakers.

Cite This Study

Murat Çuhadar (2025) studied this question.

synapsesocial.com/papers/689522129f4f1c896c429b7chttps://doi.org/10.30519/ahtr.1542430
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Also Consider

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  4. 4Automated Sentiment Analysis in Tourism: Comparison of Approaches2017 · 203 citations