COMPRENSIÓN DE LOS IMPACTOS Y LAS MOTIVACIONES DE LAS RESEÑAS DUPLICADAS EN TRIPADVISOR
Resumen
TripAdvisor es una plataforma de reseñas, donde los usuarios publican reseñas para el mismo lugar, incluidas las reseñas duplicadas. Esta duplicación puede sesgar los resultados de la investigación y las percepciones de los visitantes. Para abordar este problema, analizamos las reseñas de TripAdvisor en 3 idiomas de 20 atracciones en 2 ciudades declaradas Patrimonio de la Humanidad por la UNESCO. Identificamos 3 tipos de motivaciones para las revisiones múltiples: cuestiones hedónicas, utilitarias y editoriales. Nuestro estudio recomienda que las plataformas de revisión en línea implementen estrategias para mitigar esto y asesora a los investigadores sobre cómo superar las revisiones duplicadas en su investigación.
Descargas
Citas
ANTONIO, N., ALMEIDA, A. DE, NUNES, L., BATISTA, F. and RIBEIRO, R. (2018a): «Hotel online reviews: Different languages, different opinions», Information Technology and Tourism, vol. 18 (1-4), pp. 157-185. https://doi.org/10.1007/s40558-018-0107-x
ANTONIO, N., ALMEIDA, A. DE, NUNES, L., BATISTA, F. and RIBEIRO, R. (2018b): «Hotel online reviews: Creating a multi-source aggregated index», International Journal of Contemporary Hospitality Management, vol. 30 (12), pp. 3574-3591. https://doi.org/10.1108/IJCHM-05-2017-0302
ANTONIO, N., CORREIA, M. B. and RIBEIRO, F.P. (2020): «Exploring User-Generated Content for Improving Destination Knowledge: The Case of Two World Heritage Cities», Sustainability, vol. 12 (22), 9654. https://doi.org/10.3390/su12229654
BANERJEE, S. and CHUA, A.Y.K. (2021): «Calling out fake online reviews through robust epistemic belief», Information and Management, vol. 58 (3), 103445. https://doi.org/10.1016/j.im.2021.103445
BEN KHALIFA, M., ELOUEDI, Z. and LEFÈVRE, E. (2020): «Multiple Criteria Fake Reviews Detection Using Belief Function Theory», In A. ABRAHAM, A. K. CHERUKURI, P. MELIN and N. GANDHI (Eds.), Intelligent Systems Design and Applications (pp. 315-324), Springer International Publishing. https://doi.org/10.1007/978-3-030-16657-1_29
BERK, R. A. and FREEMAN, D.A. (2009): «Statistical assumptions as empirical commitments», In D. COLLIER, J.S. SEKHON and P.B. STARK (Eds.), Statistical Models and Causal Inference: A Dialogue with the Social Sciences, Cambridge University Press. https://doi.org/10.1017/CBO9780511815874
CANTALLOPS, A.S. and SALVI, F. (2014): «New consumer behavior: A review of research on eWOM and hotels», International Journal of Hospitality Management, vol. 36, pp. 41-51. https://doi.org/10.1016/j.ijhm.2013.08.007
CHATTERJEE, S., GOYAL, D., PRAKASH, A. and SHARMA, J. (2021): «Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application», Journal of Business Research, no. 131, pp. 815-825. https://doi.org/10.1016/j.jbusres.2020.10.043
CHEN, C.-C. and SCHWARTZ, Z. (2010): «The Impact of hedonic and utilitarian motivations on the hotel customers’ risk perception», Emerging Issues and Trends in Hospitality and Tourism Research, Paper 5. http://digitalscholarship.unlv.edu/hhrc/2010/june2010/5/
CHEN, L., LI, W., CHEN, H. and GENG, S. (2019): «Detection of Fake Reviews: Analysis of Sellers’ Manipulation Behavior», Sustainability, vol. 11 (17), 4802. https://doi.org/10.3390/su11174802
CHEN, Y.-F. and LAW, R. (2016): «A review of research on electronic word-of-mouth in hospitality and tourism management», International Journal of Hospitality and Tourism Administration, vol. 17 (4), pp. 347-372. https://doi.org/10.1080/15256480.2016.1226150
CHOI, S., MATTILA, A. S., VAN HOOF, H. B. and QUADRI-FELITTI, D. (2017): «The Role of Power and Incentives in Inducing Fake Reviews in the Tourism Industry», Journal of Travel Research, vol. 56 (8), pp. 975-987. https://doi.org/10.1177/0047287516677168
DÍAZ, M.R. and RODRÍGUEZ, T.F.E. (2018): «Determining the reliability and validity of online reputation databases for lodging: Booking.com, TripAdvisor, and Holiday Check», Journal of Vacation Marketing, vol. 24 (3), pp. 261-274. https://doi.org/10.1177/1356766717706103
DUNHAM, K, and MELNICK, J. (2009): «Malicious bots: An Inside look into the cyber-criminal underground of the internet», CRC Press.
FESTINGER, L. (1954): «A theory of social comparison processes», Human Relations, vol. 7 (2), pp. 117-140.
FILIERI, R., ALGUEZAUI, S. and MCLEAY, F. (2015): «Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth», Tourism Management, vol. 51, pp. 174-185. https://doi.org/10.1016/j.tourman.2015.05.007
GOFFMAN, E. (1959): The presentation of self in everyday life, Doubleday.
GÖSSLING, S., HALL, C.M. and ANDERSSON, A.-C. (2018): «The manager’s dilemma: A conceptualization of online review manipulation strategies», Current Issues in Tourism, vol. 21 (5), pp. 484-503. https://doi.org/10.1080/13683500.2015.1127337
HEYDARI, A., TAVAKOLI, M. ALI, SALIM, N. and HEYDARI, Z. (2015): «Detection of review spam: A survey», Expert Systems with Applications, vol. 42 (7), pp. 3634-3642. https://doi.org/10.1016/j.eswa.2014.12.029
KAC, M. (1959): «Statistical independence in probability, analysis and number theory», The Mathematical Association of America.
KRUSKAL, W. (1988): «Miracles and statistics: The casual assumption of independence», Journal of the American Statistical Association, vol. 83 (404), pp. 929-940. https://doi.org/10.1080/01621459.1988.10478682
KURIAKOSE, N. and ROBBINS, M. (2016): «Don’t get duped: Fraud through duplication in public opinion surveys», Statistical Journal of the IAOS, vol. 32 (3), pp. 283-291. https://doi.org/10.3233/SJI-160978
KWOK, L., XIE, K.L. and RICHARDS, T. (2017): «Thematic framework of online review research: A systematic analysis of contemporary literature on seven major hospitality and tourism journals», International Journal of Contemporary Hospitality Management, vol. 29 (1), pp. 307-354. https://doi.org/10.1108/IJCHM-11-2015-0664
LAU, R.Y.K., LIAO, S.Y., KWOK, R.C.-W., XU, K., XIA, Y. and LI, Y. (2011): «Text mining and probabilistic language modelling for online review spam detection», ACM Transactions on Management Information Systems, vol. 2 (4), pp. 1-30. https://doi.org/10.1145/2070710.2070716
LI, H., MENG, F. and HUDSON, S. (2023): «Are Hotel Guests Altruistic? How Positive Review Disconfirmation Affects Consumers’ Online Review Behavior», Journal of Hospitality and Tourism Research, 47(3), 528-548. https://doi.org/10.1177/10963480211030313
LI, J., OTT, M., CARDIE, C. and HOVY, E. (2014): «Towards a general rule for identifying deceptive opinion spam», In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Vol. 1: Long Papers), pp.1566-1576, Baltimore, Maryland. Association for Computational Linguistics.
LI, L., LEE, K. Y., LEE, M. and YANG, S.-B. (2020): «Unveiling the cloak of deviance: Linguistic cues for psychological processes in fake online reviews», International Journal of Hospitality Management, vol. 87, 102468. https://doi.org/10.1016/j.ijhm.2020.102468
LIN, Y., ZHU, T., WANG, X., ZHANG, J. and ZHOU, A. (2014): «Towards online review spam detection», In Proceedings of the 23rd International Conference on World Wide Web - WWW ’14 Companion, pp. 341-342. https://doi.org/10.1145/2567948.2577293
MAYZLIN, D., DOVER, Y. and CHEVALIER, J. (2014): «Promotional Reviews: An Empirical Investigation of Online Review Manipulation», American Economic Review, vol. 104 (8), pp. 2421-2455. https://doi.org/10.1257/aer.104.8.2421
OLIVEIRA, A.S., RENDA, A.I., CORREIA, M.B. and ANTONIO, N. (2022): «Hotel customer segmentation and sentiment analysis through online reviews: an analysis of selected European markets», Tourism and Management Studies, vol. 18 (1), pp. 29-40. https://doi.org/10.18089/tms.2022.180103
OLIVER, R.L. (1980): «A cognitive model of the antecedents and consequences of satisfaction decisions», Journal of Marketing Research, vol. 17 (4), pp. 460-469.
PETRESCU, M., O’LEARY, K., GOLDRING, D. and BEN MRAD, S. (2018): «Incentivized reviews: Promising the moon for a few stars», Journal of Retailing and Consumer Services, vol. 41, pp. 288-295. https://doi.org/10.1016/j.jretconser.2017.04.005
PYLE, M.A., SMITH, A.N. and CHEVTCHOUK, Y. (2021): «In eWOM we trust: Using naïve theories to understand consumer trust in a complex eWOM marketspace», Journal of Business Research, vol. 122, pp. 145-158. https://doi.org/10.1016/j.jbusres.2020.08.063
R CORE TEAM. (2016): «R: A language and environment for statistical computing», R Foundation for Statistical Computing. https://www.R-project.org/
ROSS, L. (1977): The Intuitive Psychologist and His Shortcomings: Distortions in the Attribution Process. In L. BERKOWITZ (Ed.), Advances in Experimental Social Psychology (pp. 173-220). New York: Academic Press.
RYAN, R. M. and DECI, E. L. (2000): «Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being», American Psychologist, vol. 55 (1), pp. 68-78.
SALEHI-ESFAHANI, S. and OZTURK, A. B. (2018): «Negative reviews: Formation, spread, and halt of opportunistic behaviour», International Journal of Hospitality Management, vol. 74, pp. 138-146. https://doi.org/10.1016/j.ijhm.2018.06.022
SARRACINO, F. and MIKUCKA, M. (2017): «Bias and efficiency loss in regression estimates due to duplicated observations: A Monte Carlo simulation», Survey Research Methods, vol. 11 (1). https://doi.org/10.18148/srm/2017.v11i1.7149
TAJFEL, H. and TURNER, J. C. (1979): «An integrative theory of intergroup conflict», In W. G. Austin and S. Worchel (Eds.), The social psychology of intergroup relations (pp. 33-47). Brooks/Cole.
THAKUR, R., HALE, D. and SUMMEY, J. H. (2018): «What Motivates Consumers to Partake in Cyber Shilling?», Journal of Marketing Theory and Practice, vol. 26 (1-2), pp. 181-195. https://doi.org/10.1080/10696679.2017.1389236
TRIPADVISOR. (n.d.-a): «How often can I write a review?», TripAdvisor Help Center. Retrieved August 16, 2022, from http://www.tripadvisorsupport.com/hc/en-us/articles/200614897-How-often-can-I-write-a-review-
TRIPADVISOR. (n.d.-b): «Why isn’t my review posted yet?», TripAdvisor Help Center. Retrieved August 16, 2022, from http://www.tripadvisorsupport.com/hc/en-us/articles/200614817-Why-isn-t-my-review-posted-yet-
TRIPADVISOR. (2017, September 11): «All about your TripAdvisor bubble rating», TripAdvisor. https://www.tripadvisor.com/TripAdvisorInsights/w810
VELICIA-MARTIN, F., FOLGADO-FERNANDEZ, J.A., PALOS-SANCHEZ, P. and LOPEZ-CATALAN, B. (2022): «MWOM business strategies: Factors affecting recommendations», Journal of Computer Information Systems, 2041504. https://doi.org/10.1080/08874417.2022.2041504
WALTHER M., JAKOBI T., WATSON S.J. and STEVENS G. (2023): «A systematic literature review about the consumers’ side of fake review detection - Which cues do consumers use to determine the veracity of online user reviews?», Computers in Human Behavior Reports, vol. 10. https://doi.org/10.1016/j.chbr.2023.100278
WICKHAM, H., FRANÇOIS, R., HENRY, L. and MÜLLER, K. (2018): «dplyr: A grammar of data manipulation (R package version 0.7.8)». https://CRAN.R-project.org/package=dplyr
Las obras que se publican en esta revista están sujetas a los siguientes términos:
1. El Servicio de Publicaciones de la Universidad de Murcia (la editorial) conserva los derechos patrimoniales (copyright) de las obras publicadas, y favorece y permite la reutilización de las mismas bajo la licencia de uso indicada en el punto 2.
2. Las obras se publican en la edición electrónica de la revista bajo una licencia Creative Commons Reconocimiento-NoComercial-SinObraDerivada 3.0 España (texto legal). Se pueden copiar, usar, difundir, transmitir y exponer públicamente, siempre que: i) se cite la autoría y la fuente original de su publicación (revista, editorial y URL de la obra); ii) no se usen para fines comerciales; iii) se mencione la existencia y especificaciones de esta licencia de uso.
3. Condiciones de auto-archivo. Se permite y se anima a los autores a difundir electrónicamente las versiones pre-print (versión antes de ser evaluada) y/o post-print (versión evaluada y aceptada para su publicación) de sus obras antes de su publicación, ya que favorece su circulación y difusión más temprana y con ello un posible aumento en su citación y alcance entre la comunidad académica. Color RoMEO: verde.