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Textual analysis as a method of identifying museum attributes perceived by tourists: An exploratory analysis of Thyssen-Bornemisza National Museum in Spain

Author

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  • Alicia Orea-Giner

    (URJC - Universidad Rey Juan Carlos = Rey Juan Carlos University, EIREST - Équipe interdisciplinaire de recherches sur le tourisme - UP1 - Université Paris 1 Panthéon-Sorbonne)

  • Trinidad Vacas Guerrero

Abstract

Objective: The identification of museum attributes is essential when analysing the different factors that attract visitors and studying it in order to improve efficiency in museums, as this could affect the use of funds for developing a marketing campaign to attract visitors. This paper offers a literature review that considers museum visits and museum attributes before proposing a methodology. Methodology: The use of big data applied to tourism research is vital, as it allows for the consideration of the opinions of museum visitors. The case study in this paper is the Thyssen-Bornemisza National Museum in Madrid, Spain. The method for identifying the attributes consists of a textual analysis of TripAdvisor reviews written in English (2500) and Spanish (2500). The information is captured using WebHarvy and is analysed using Nvivo12. Results: After analysing the thousand words that were used most frequently, the main attributes were detected, as well as whether the perception of these attributes was positive or negative. The museum's location and the building itself were the most highly valued attributes. Other attributes that were valued positively were the peripheral services of the museum, such as its food and beverage services. Limitations: The main limitation is that TripAdvisor is not an entirely reliable source of information, so it will be necessary to obtain more reviews to analyse.

Suggested Citation

  • Alicia Orea-Giner & Trinidad Vacas Guerrero, 2020. "Textual analysis as a method of identifying museum attributes perceived by tourists: An exploratory analysis of Thyssen-Bornemisza National Museum in Spain," Post-Print hal-04039224, HAL.
  • Handle: RePEc:hal:journl:hal-04039224
    DOI: 10.7200/esicm.167.0513.2
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    Cited by:

    1. Alicia Orea-Giner & Laura Fuentes-Moraleda & Teresa Villacé-Molinero & Ana Muñoz-Mazón & Jorge Calero-Sanz, 2022. "Does the Implementation of Robots in Hotels Influence the Overall TripAdvisor Rating? A Text Mining Analysis from the Industry 5.0 Approach," Post-Print hal-04039195, HAL.

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