Influencers virtuales humanizados: actitudes y percepciones humanas y actitudes ante un fenómeno emergente
DOI:
https://doi.org/10.31637/epsir-2024-657Palabras clave:
influencer virtual, inteligencia artificial, redes sociales, marketing de influencers, percepción, emoción, actitud, InstagramResumen
Introducción: La evolución tecnológica ha dado lugar a influencers virtuales, figuras creadas digitalmente que participan en redes sociales digitales para captar la atención de los cibernautas con fines comerciales. Estos influencers se vuelven cada vez más sofisticados y pretenden un alto parecido al ser humano. El objetivo general de este estudio es comprender cómo los influencers virtuales parecidos al ser humano influyen en la percepción, las emociones y en la actitud de la población cibernauta humana. Estos constructos conforman el modelo conceptual a medir. Metodología: El diseño conclusivo descriptivo utiliza una metodología mixta incluye: una encuesta en línea aplicada a 1.380 usuarios; y el análisis de contenido de 47.500 interacciones en Instagram. Resultados: Los resultados confirman que la existencia de los influencers virtuales, sobre todo los más antropomorfos, tiene efecto en la percepción y emoción humana. Discusión: La interacción entre humanos y entes virtuales va en aumento. La discusión se enfoca en la interacción entre humanos y entes virtuales va en aumento, los distintos efectos en los primeros deben observarse. Conclusiones: Se reconoce el papel de los influencer virtuales en el marketing de influencers; sin embargo, aún deben observarse las cuestiones éticas y sociales sucedidas en interacciones sociales en entornos digitales.
Descargas
Citas
Arsenyan, J., & Mirowska, A. (2021). Almost human? A comparative case study on the social media presence of virtual influencers. International Journal of Human-Computer Studies, 155, 102694. https://doi.org/10.1016/j.ijhcs.2021.102694 DOI: https://doi.org/10.1016/j.ijhcs.2021.102694
Bank of America & Merryl Lynch Report (2016). Thematic investing: New Kids on the Block. https://tinyurl.com/2hcnjfhe
Da Silva Oliveira, A. B., & Chimenti, P. (2021). "Humanized Robots": A Proposition of Categories to Understand Virtual Influencers. Australasian Journal of Information Systems, 25. https://doi.org/10.3127/ajis.v25i0.3223 DOI: https://doi.org/10.3127/ajis.v25i0.3223
Brody, L. R. (1999). Gender, emotion, and the family. Harvard University Press. DOI: https://doi.org/10.4159/9780674028821
Byrne, B. M. (2013). Structural Equation Modeling with EQS: Basic Concepts, Applications, and Programming (2nd ed.). Routledge. DOI: https://doi.org/10.4324/9780203807644
Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014, September). The use of triangulation in qualitative research. Oncology Nursing Forum, 41(5), 545-547. https://doi.org/10.1188/14.ONF.545-547 DOI: https://doi.org/10.1188/14.ONF.545-547
Casaló, L. V., Flavián, C., & Ibáñez-Sánchez, S. (2020). Influencers on Instagram: Antecedents and consequences of opinion leadership. Journal of Business Research, 117, 510-519. https://doi.org/10.1016/j.jbusres.2018.07.005 DOI: https://doi.org/10.1016/j.jbusres.2018.07.005
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37-46. https://doi.org/10.1177/001316446002000104 DOI: https://doi.org/10.1177/001316446002000104
Cong, L. W., & Li, S. (2024). Influencer marketing and product competition. Journal of Economic Theory, 105867. https://doi.org/10.1016/j.jet.2024.105867 DOI: https://doi.org/10.1016/j.jet.2024.105867
Davlembayeva, D., Chari, S., & Papagiannidis, S. (2024). Virtual influencers in consumer behaviour: A social influence theory perspective. British Journal of Management. https://doi.org/10.1111/1467-8551.12839 DOI: https://doi.org/10.1111/1467-8551.12839
Dencheva, V. (2024, February 6th). Global influencer market size 2024. Statista. https://tinyurl.com/22xu3427
Denzin, N. K. (1984). On understanding emotion. Transaction Publishers.
Dixon, S. J. (2024a, May 2nd). Distribution of Instagram users worldwide as of April 2024, by age group. Statista. https://tinyurl.com/ymuzprfy
Dixon, S. J. (2024b, May 2nd). Instagram: Countries with the highest audience reach 2024. Statista. https://tinyurl.com/bdhy7pxc
Djafarova, E., & Rushworth, C. (2017). Exploring the credibility of online celebrities' Instagram profiles in influencing the purchase decisions of young female users. Computers in Human Behavior, 68, 1-7. https://doi.org/10.1016/j.chb.2016.11.009 DOI: https://doi.org/10.1016/j.chb.2016.11.009
Edwards, C., Beattie, A. J., Edwards, A., & Spence, P. R. (2016). Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning. Computers in Human Behavior, 65, 666-671. https://doi.org/10.1016/j.chb.2016.07.003 DOI: https://doi.org/10.1016/j.chb.2016.07.003
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104 DOI: https://doi.org/10.1177/002224378101800104
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning.
Hanus, M. D., & Fox, J. (2015). Persuasive avatars: The effects of customizing a virtual salesperson׳ s appearance on brand liking and purchase intentions. International Journal of Human-Computer Studies, 84, 33-40. https://doi.org/10.1016/j.ijhcs.2015.07.004 DOI: https://doi.org/10.1016/j.ijhcs.2015.07.004
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118 DOI: https://doi.org/10.1080/10705519909540118
Jasper, J. M. (2011). Emotions and social movements: Twenty years of theory and research. Annual Review of Sociology, 37, 285-303. https://doi.org/10.1146/annurev-soc-081309-150015 DOI: https://doi.org/10.1146/annurev-soc-081309-150015
Kemper, T. D. (1987). How many emotions are there? Wedding the social and the autonomic components. American Journal of Sociology, 93(2), 263-289. https://doi.org/10.1086/228745 DOI: https://doi.org/10.1086/228745
Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford Press.
Kozinets, R. V. (2002). The field behind the screen: Using netnography for marketing research in online communities. Journal of Marketing Research, 39(1), 61-72. https://doi.org/10.1509/jmkr.39.1.61.18935 DOI: https://doi.org/10.1509/jmkr.39.1.61.18935
Lim, R. E., & Lee, S. Y. (2023). “You are a virtual influencer!”: Understanding the impact of origin disclosure and emotional narratives on parasocial relationships and virtual influencer credibility. Computers in Human Behavior, 148, 107897. DOI: https://doi.org/10.1016/j.chb.2023.107897
Lou, C., Kiew, S. T. J., Chen, T., Lee, T. Y. M., Ong, J. E. C., & Phua, Z. (2023). Authentically fake? How consumers respond to the influence of virtual influencers. Journal of Advertising, 52(4), 540-557. https://doi.org/10.1080/00913367.2022.2149641 DOI: https://doi.org/10.1080/00913367.2022.2149641
Partala, T. (2011). Psychological needs and virtual worlds: Case Second Life. International Journal of Human-Computer Studies, 69(12), 787-800. https://doi.org/10.1016/j.ijhcs.2011.07.004 DOI: https://doi.org/10.1016/j.ijhcs.2011.07.004
Rodríguez, M. N., & Ruiz, M. A. (2008). Atenuación de la asimetría y de la curtosis de las puntuaciones observadas mediante transformaciones de variables: Incidencia sobre la estructura factorial. Psicológica, 29(2), 205-227. https://tinyurl.com/mv2ek87r
Scherer, K. R. (2001). Appraisal considered as a process of multilevel sequential checking. In K. R. Scherer, A. Schorr, & T. Johnstone (Eds.), Appraisal processes in emotion: Theory, methods, research (pp. 92-120). Oxford University Press. DOI: https://doi.org/10.1093/oso/9780195130072.003.0005
Sheinin, D. A., Varki, S., & Ashley, C. (2011). The differential effect of ad novelty and message usefulness on brand judgments. Journal of Advertising, 40(3), 5-18. https://doi.orKimg/10.2753/JOA0091-3367400301 DOI: https://doi.org/10.2753/JOA0091-3367400301
Sheldon, P., & Bryant, K. (2016). Instagram: Motives for its use and relationship to narcissism and contextual age. Computers in Human Behavior, 58, 89-97. https://doi.org/10.1016/j.chb.2015.12.059 DOI: https://doi.org/10.1016/j.chb.2015.12.059
Stryker, S. (2004). Integrating emotion into identity theory. In J. H. Turner (Ed.), Advances in group processes, 21. Theory and research on human emotions (pp. 1-23). Elsevier Science/JAI Press. https://doi.org/10.1016/S0882-6145(04)21001-3 DOI: https://doi.org/10.1016/S0882-6145(04)21001-3
Turpo, O. W. (2008). La netnografía: un método de investigación en Internet. Educar, 42, 81-93. https://doi.org/10.5565/rev/educar.134 DOI: https://doi.org/10.5565/rev/educar.134
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2024 Mónica Pérez-Sánchez, Javier Casanoves-Boix, Betzabeth Dafne Morales
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Non Commercial, No Derivatives Attribution 4.0. International (CC BY-NC-ND 4.0.), that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Datos de los fondos
-
Universidad de Guanajuato
Números de la subvención 60.000