Ir al contenido

Documat


¿Cómo perciben los visitantes los museos de Lambayeque (Perú)? Un análisis de sentimiento basado en reseñas de Tripadvisor

  • Marco Antonio Soto Rumiche [1] ; José Luis Caro Herrero [1]
    1. [1] Universidad de Málaga

      Universidad de Málaga

      Málaga, España

  • Localización: Revista del Museo de Antropología, ISSN 1852-060X, ISSN-e 1852-4826, Vol. 19, Nº. 1, 2026, págs. 171-184
  • Idioma: español
  • DOI: 10.31048/8trhpq16
  • Títulos paralelos:
    • How do visitors perceive museums in Lambayeque (Peru)? A sentiment analysis based on Tripadvisor reviews
  • Enlaces
  • Resumen
    • español

      El presente estudio analiza la percepción de los visitantes sobre los principales museos de Lambayeque (Perú) mediante un análisis de sentimientos aplicado a reseñas de Tripadvisor. Mediante técnicas de procesamiento del lenguaje natural (PLN) y de minería de texto, se identificaron patrones semánticos y tendencias en la opinión de los usuarios, lo que permitió una evaluación empírica de la experiencia museística regional. La investigación museológica en el Perú continúa siendo incipiente, especialmente fuera de Lima, y son escasos los estudios sobre públicos de museo; aún más limitados son aquellos que examinan percepciones expresadas en plataformas digitales como Tripadvisor. En este contexto, el presente trabajo constituye una contribución pionera para comprender la reputación en línea de los museos lambayecanos. Los resultados evidencian una percepción predominantemente positiva, destacando términos como “mejor”, “interesante” y “arqueológico”, asociados a la oferta museística y al reconocimiento del valor patrimonial y educativo. Asimismo, se observa una valoración favorable del equilibrio entre la preservación del legado prehispánico y la implementación de tecnologías museográficas contemporáneas. No obstante, la baja frecuencia de términos vinculados a la accesibilidad sugiere la necesidad de fortalecer la inclusión de personas con movilidad reducida.

    • English

      This study analyses visitors’ perceptions of the main museums in Lambayeque (Peru) through a sentiment analysis of Tripadvisor reviews. Using natural language processing (NLP) and text mining techniques, semantic patterns and trends in user opinions were identified, enabling an empirical assessment of the regional museum experience. Museum research in Peru remains in its infancy, particularly outside Lima, and studies on museum audiences are scarce; even fewer examine perceptions expressed on digital platforms such as Tripadvisor. In this context, this study represents a pioneering contribution to understanding the online reputation of museums in Lambayeque. The results reveal a predominantly positive perception, highlighting terms such as ‘best’, ‘interesting’ and ‘archaeological’, associated with the museum offering and the recognition of heritage and educational value. Furthermore, a favourable assessment is observed of the balance between the preservation of pre-Hispanic heritage and the implementation of contemporary museographic technologies. However, the low frequency of accessibility-related terms suggests a need to improve inclusion for people with reduced mobility.

  • Referencias bibliográficas
    • Aakash, G.S., y Noliya, A. (2024). URL-Based Sentiment Analysis of Product Reviews Using LSTM and GRU. Procedia Computer Science, 235, 1814–1823....
    • Agüero-Torales, M. M., Cobo, M. J., Herrera-Viedma, E., y López-Herrera, A. G. (2019). A cloud-based tool for sentiment analysis in reviews...
    • Alizadeh, A., y Isa, R. M. (2015). The use of social media in destination marketing: An exploratory study. Tourism, 63(2), 175–192. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937419645&partnerID=40&md5=7b563076acaeac8498e40318cdd68585
    • Al-Saffar, M., y Anissa Tabet Aoul, K. (2019). Visitors Voice in Historic Sites Interpretation Centres in Bahrain. IOP Conference Series:...
    • Bakare, A. M., Anbananthen, K. S. M., Muthaiyah, S., Krishnan, J., y Kannan, S. (2023). Punctuation Restoration with Transformer Model on...
    • Bastidas Manzano, A. B., Sánchez Fernández, J., y Casado Aranda, L. A. (2018). La influencia de la web en la reputación online: el caso de...
    • Bikku, T., Jarugula, J., Kongala, L., Tummala, N. D., y Donthiboina, N. V. (2023). Exploring the Effectiveness of BERT for Sentiment Analysis...
    • Bose, R., Dey, R., Roy, S., y Sarddar, D. (2018). Sentiment Analysis on Online Product Reviews.
    • Catir, O. (2024). Determining the experience of museum visitors by text mining: example of Topkapi Palace museum. International Journal of...
    • Chen, X., Chen, Z., Xiao, L., y Zhou, M. (2022). A Novel Sentiment Analysis Model of Museum User Experience Evaluation Data Based on Unbalanced...
    • Chen, Y., Hong, C., Yang, Y., Li, J., Wang, Y., Zheng, T., Zhang, Y., y Shao, F. (2024). Mining Social Media Data to Capture Urban Park Visitors’...
    • Cocón, F., Pérez-Cruz, D., Pérez-Rejón, J. Á., Zavaleta-Carrillo, P., Barradas-Arenas, U., Gómez-Ramón, R., y Cruz, J. A. P. (2023). Web scraping:...
    • Dagar, V., Verma, A., y Govardhan, K. (2020). Sentiment Analysis and Sarcasm Detection (Using Emoticons). In Applications of Artificial Intelligence...
    • Divaker, R. M., y Kerr, M. M. (2023). Revealing reviews: employing Tripadvisor to explore children’s experiences at medical museums. Journal...
    • Doborjeh, Z., Hemmington, N., Doborjeh, M., y Kasabov, N. (2022). Artificial intelligence: a systematic review of methods and applications...
    • Ferdous, S. M., Newaz, S. N. E., Mugdha, S. B. S., y Uddin, M. (2025a). Sentiment Analysis in the Transformative Era of Machine Learning:...
    • Ferdous, S. M., Newaz, S. N. E., Mugdha, S. B. S., y Uddin, M. (2025b). Sentiment Analysis in the Transformative Era of Machine Learning:...
    • Fernández-Hernández, R., Vacas-Guerrero, T., y García-Muiña, F. E. (2021). Online reputation and user engagement as strategic resources of...
    • Flores, J. C. M., y Valenzuela, J. P. V. (2023a). Data mining for sentiment analysis: a case study. New Trends in Qualitative Research, 19,...
    • Flores, J. C. M., y Valenzuela, J. P. V. (2023b). Data mining for sentiment analysis: a case study. New Trends in Qualitative Research, 19,...
    • Franciele, C., Christina, T., Ruiz, D., Manosso, F. C., y Cristina, T. (2021). Using sentiment analysis in tourism research: A systematic,...
    • Garg, S., Singh, P., y Singh, N. (2021). Sentimental Analysis, Technology and Application. 2021 3rd International Sustainability and Resilience...
    • Hernández, R., y Arista, A. (2011). Turismo, museos y desarrollo rural ¿Por quién y para quién? (IEP). Instituto de Estudios Peruanos.
    • Higuchi, K. (2016). A Two-Step Approach to Quantitative Content Analysis - KH Coder Tutorial using Anne of Green Gables (Part I). Ritsumeikan...
    • Higuchi, K. (2017). KH Coder 3 Reference Manual.
    • Hussain, T., Li, B., y Wang, D. (2018). What factors influence the sustainable tour process in social media usage? Examining a rural mountain...
    • Jingwen, Z., y Lin, L. (2023). Limitations and ethical reflection on the application of big data in museum visitor research. Museum Management...
    • Kasthuriarachchy, B. H., Zoysa, K. de, y Premarathne, H. L. (2015). Context-aware sentiment classification. 2015 Fifteenth International Conference...
    • Kazimierczak, M., y Rozmiarek, M. (2021). Krajoznawstwo in times of climate change. Sport i Turystyka, 4(4), 145–157. https://doi.org/10.16926/sit.2021.04.31
    • Kim, R. Y. (2021). Using Online Reviews for Customer Sentiment Analysis. IEEE Engineering Management Review, 49(4), 162–168. https://doi.org/10.1109/EMR.2021.3103835
    • Kydros, D., y Vrana, V. (2021). A Twitter network analysis of European museums. Museum Management and Curatorship, 36(6), 569–589. https://doi.org/10.1080/09647775.2021.1894475
    • Lekmiti, A., Stolk, P. J., Taylor, A., Ramachandran, S., y Yap, N. K. (2024). Text mining in tourism and hospitality research: a bibliometric...
    • Liang, F., Pan, Y., Gu, M. L., Guan, W. H., y Tsai, F. S. (2021). Cultural Tourism Resource Perceptions: Analyses Based on Tourists’ Online...
    • Magliacani, M., Madeo, E., y Cerchiello, P. (2018). From ‘listener’ to ‘speaker’ museum visitors: guest book as a means of dialogue. Museum...
    • Medina-Hernandez, V. C., Marine-Roig, E., y Ferrer-Rosell, B. (2024). Attributes influencing guests’ experiences: a comparison of nonprofit...
    • Ministerio de Cultura del Perú. (2024). Memoria Anual 2023.
    • Morlà, C. G., y García, M. R. (2022). Museums, collective memory and narrative imaginaries. Participatory communication as a strategy for...
    • Nalini, C., Dharani, B., Baskar, T., y Shanthakumari, R. (2023a). Review on Sentiment Analysis Using Supervised Machine Learning Techniques....
    • Nalini, C., Dharani, B., Baskar, T., y Shanthakumari, R. (2023b). Review on Sentiment Analysis Using Supervised Machine Learning Techniques....
    • Nilashi, M., Ali Abumalloh, R., Alrizq, M., Alghamdi, A., Samad, S., Almulihi, A., Althobaiti, M. M., Yousoof Ismail, M., y Mohd, S. (2022)....
    • Orrego, C., Villa, L. F., Sepúlveda-Cano, L. M., y Giraldo M, L. M. (2021). Organizational Online Reputation Measurement Through Natural Language...
    • Pozzi, F. A., Fersini, E., Messina, E., y Liu, B. (2016). Sentiment Analysis in Social Networks. https://api.semanticscholar.org/CorpusID:64181655
    • Prasanthi, K. N., Chandrasekhararao, M. V. P., Chekuri, S., y Babu, S. P. (2024). Sentiment mining of customer reviews from e-commerce websites....
    • Raj, V. (2019). Sentiment Analysis on Product Reviews. Proceedings - 2019 International Conference on Computing, Communication, and Intelligent...
    • Ramírez-Gutiérrez, D. (2023). Memories in quarantine: reconstructing museum visitors’ experiences in uncertain times. Museum Management and...
    • Richmond, F., Uchechukwu, N. C., y Ramos, C. M. (2023). Analyses of visitors’ experiences in museums based on e-word of mouth and tripadvisors...
    • Sharma, M. P., Meena, U., y Sharma, G. K. (2022). Intelligent Data Analysis using Optimized Support Vector Machine Based Data Mining Approach...
    • Sindhu, S., Kumar, S., y Noliya, A. (2023). A Review on Sentiment Analysis using Machine Learning. International Conference on Innovative...
    • Sousa, B. B., Castro, C., Luís, M. E., y Lopes, P. (2020). Religious and spiritual tourism: From its origins to Alentejo (Portugal). In Global...
    • Su, Y., y Teng, W. (2018). Contemplating museums’ service failure: Extracting the service quality dimensions of museums from negative on-line...
    • Taecharungroj, V., y Mathayomchan, B. (2019). Analysing TripAdvisor reviews of tourist attractions in Phuket, Thailand. Tourism Management,...
    • Tapanainen, T., Dao, T. K., y Nguyen, T. T. H. (2021). Impacts of online word-of-mouth and personalities on intention to choose a destination....
    • Turner, B. L., y Klaus, H. D. (2020). The Lambayeque Biohistory Project: Contexts and Analysis. In Bioarchaeology and Social Theory, 85–111....
    • Vrana, V., Zafiropoulos, K., y Antoniadis, K. (2016). Top European Museums on Twitter. Springer Proceedings in Business and Economics, 457–469....
    • Wang, H., Song, C., y Li, H. (2024). Application of social media communication for museum based on the deep mediatization and artificial intelligence....
    • Wang, Q., Ch’ng, E., Xu, X. S., Wang, J., y Zhang, Y. F. (2024). Perception and gaze of diaspora: Analysis of affective, cognitive, &...
    • Yadav, N., Kumbhar, R., Goves, A., Coelho, C., Rebello, I., Mahale, S., Wadekar, A., y Aswale, S. (2023). Sentiment Analysis for Product Reviews...
    • Yingming, M., y Katsunori, F. (2019). Study of perception of Japanese garden using LIST and KH Coder Method among people in European. In Geophysical...
    • Zhang, T. T., Li, B., y Hua, N. (2022). Chinese cultural theme parks: text mining and sentiment analysis. JOURNAL OF TOURISM AND CULTURAL...

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno