Lyrical and Instrumental Music on TikTok
Attention, Emotion and Social Virality
DOI:
https://doi.org/10.62161/revvisual.v18.6281Keywords:
Neuromarketing, Electrodermal activity (EDA), Audiovisual attention, Implicit emotional engagement, Music typology, Social virality, TikTokAbstract
The study examines the differential impact of lyrical versus instrumental music on cognitive-emotional processing and the social diffusion of audiovisual content on TikTok. Using a multimethod experimental design, the research integrates electrodermal activity (EDA), automated facial expression analysis, post-exposure declarative responses, and real platform interaction metrics. Results indicate that instrumental music fosters more sustained physiological attention, whereas lyrical music enhances conscious evaluation and visible engagement. Moreover, partial dissociations emerge between implicit emotional activation and behavioral virality.
Downloads
Global Statistics ℹ️
|
82
Views
|
62
Downloads
|
|
144
Total
|
|
References
Allan, D. (2008). A content analysis of music placement in prime-time television advertising. Journal of Advertising Research, 48(3), 404–417. https://doi.org/10.2501/S0021849908080434 DOI: https://doi.org/10.2501/S0021849908080434
Alvino, L., Herrando, C., & Constantinides, E. (2024). Discovering the art of advertising using neuromarketing: A literature review on physiological and neurophysiological measures of ads. International Journal of Internet Marketing and Advertising, 21(3–4), 297–330. https://doi.org/10.1504/IJIMA.2024.142791 DOI: https://doi.org/10.1504/IJIMA.2024.142791
Arrieta, A. (2025). The limits of virality: Music creators and platform negotiation in the era of short-form video. Social Media + Society, 11(4), 1–13. https://doi.org/10.1177/20563051251388000 DOI: https://doi.org/10.1177/20563051251388000
Benedek, M., & Kaernbach, C. (2010). A continuous measure of phasic electrodermal activity. Journal of Neuroscience Methods, 190(1), 80–91. https://doi.org/10.1016/j.jneumeth.2010.04.028 DOI: https://doi.org/10.1016/j.jneumeth.2010.04.028
Berger, J. (2025). What gets shared, and why? Interpersonal communication and word of mouth. Annual Review of Psychology, 76, 5.1–5.23. https://doi.org/10.1146/annurev-psych-013024-031524 DOI: https://doi.org/10.1146/annurev-psych-013024-031524
Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205. https://doi.org/10.1509/jmr.10.0353 DOI: https://doi.org/10.1509/jmr.10.0353
Bigné, E., Boksem, M., Casado-Aranda, L. A., García-Madariaga, J., Gier-Reinartz, N. R., Guerreiro, J., Loureiro, S., Kakaria, S., Smidts, A., & Wedel, M. (2025). How to conduct valuable marketing research with neurophysiological tools. Psychology & Marketing, 42(10), 2616–2649. https://doi.org/10.1002/mar.70002 DOI: https://doi.org/10.1002/mar.70002
Boucsein, W. (2012). Electrodermal activity (2nd ed.). Springer. https://doi.org/10.1007/978-1-4614-1126-0 DOI: https://doi.org/10.1007/978-1-4614-1126-0
Bruner, G. C. (1990). Music, mood, and marketing. Journal of Marketing, 54(4), 94–104. https://doi.org/10.2307/1251762 DOI: https://doi.org/10.1177/002224299005400408
Dawson, M. E., Schell, A. M., & Filion, D. L. (2007). The electrodermal system. In J. T. Cacioppo, L. G. Tassinary, & G. G. Berntson (Eds.), Handbook of psychophysiology (3rd ed., pp. 159–181). Cambridge University Press. https://doi.org/10.1017/CBO9780511546396.007 DOI: https://doi.org/10.1017/CBO9780511546396.007
Eerola, T., Kirts, C., & Saarikallio, S. (2024). Episode model: The functional approach to emotional experiences of music. Psychology of Music, 53(4), 590–615. https://doi.org/10.1177/03057356241279763 DOI: https://doi.org/10.1177/03057356241279763
Ekman, P. (2007). Emotions revealed: Recognizing faces and feelings to improve communication and emotional life (2nd ed.). Henry Holt and Company.
Ekman, P., & Friesen, W. V. (1978). Facial Action Coding System: Investigator’s guide. Consulting Psychologists Press. DOI: https://doi.org/10.1037/t27734-000
Gamboa, P., Varandas, R., Mrotzeck, K., da Silva, H. P., & Quaresma, C. (2025). Electrodermal activity analysis at different body locations. Sensors, 25(6), 1762. https://doi.org/10.3390/s25061762 DOI: https://doi.org/10.3390/s25061762
Gerbaudo, P. (2025). TikTok and the algorithmic transformation of social media publics: From social networks to social interest clusters. New Media & Society. https://doi.org/10.1177/14614448241304106 DOI: https://doi.org/10.1177/14614448241304106
Hossain, M.-B., Kong, Y., Posada-Quintero, H., & Chon, K. (2024). Electrodermal activity: Applications and challenges. In The Cambridge handbook of research methods and statistics for the social and behavioral sciences (Vol. 2, pp. 475–496). Cambridge University Press. https://doi.org/10.1017/9781009000796.022 DOI: https://doi.org/10.1017/9781009000796.022
Jackson, D. M. (2003). Sonic branding: An introduction. Palgrave Macmillan. DOI: https://doi.org/10.1057/9780230503267
Juslin, P. N., & Västfjäll, D. (2008). Emotional responses to music: The need to consider underlying mechanisms. Behavioral and Brain Sciences, 31(5), 559–575. https://doi.org/10.1017/S0140525X08005293 DOI: https://doi.org/10.1017/S0140525X08005293
Kellaris, J. J., Cox, A. D., & Cox, D. (1993). The effect of background music on ad processing: A contingency explanation. Journal of Marketing, 57(4), 114–125. https://doi.org/10.2307/1252223 DOI: https://doi.org/10.1177/002224299305700409
Krishna, A. (2012). An integrative review of sensory marketing: Engaging the senses to affect perception, judgment and behavior. Journal of Consumer Psychology, 22(3), 332–351. https://doi.org/10.1016/j.jcps.2011.08.003 DOI: https://doi.org/10.1016/j.jcps.2011.08.003
Luna, A. B. M. de, & Gómez, S. M. (2025). The Three-Factor Model and Skills for Employability. Journal of Posthumanism, 5(2), 836–853. https://doi.org/10.63332/joph.v5i2.459 DOI: https://doi.org/10.63332/joph.v5i2.459
Martínez Allué, M., & Martín Cárdaba, M. Á. (2024). “Kidfluencers”: Children influencers on YouTube and TikTok. Visual Review, 16(5), 261–270. https://doi.org/10.62161/revvisual.v16.5301 DOI: https://doi.org/10.62161/revvisual.v16.5301
Martín-Guerra, E., Mielgo Álvarez, A., & Saá Teja, P. (2024). Metodologías de “marketing science” en la comunicación: Una aplicación conjunta de la universidad y la empresa. En Pensar sobre la comunicación: universidad y empresa (pp. 135–142). Tirant lo Blanch.
Martin-Neira, J. I., Irarrázaval, J., & Gómez, R. (2025). Narrativas visuales en TikTok. Visual Review, 17(2), 187–202. https://doi.org/10.62161/revvisual.v17.5757 DOI: https://doi.org/10.62161/revvisual.v17.5757
Mielgo Álvarez, A., & Saá Teja, P. (2025). El marketing science: Herramienta académica para la transferencia de conocimiento y captación del talento universitario. En E. Martín-Guerra (Ed.), Marketing science: Del dato a la estrategia (pp. 177–186). Tirant lo Blanch.
North, A. C., & Hargreaves, D. J. (2006). The effects of music on atmosphere and purchase intentions in a cafeteria. Journal of Applied Social Psychology, 28(24), 2254–2273. https://doi.org/10.1111/j.1559-1816.1998.tb01370.x DOI: https://doi.org/10.1111/j.1559-1816.1998.tb01370.x
Oakes, S. (2007). Evaluating empirical research into music in advertising: A congruity perspective. Journal of Advertising Research, 47(1), 38–50. https://doi.org/10.2501/S0021849907070055 DOI: https://doi.org/10.2501/S0021849907070055
Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013). Social media metrics. Journal of Interactive Marketing, 27(4), 281–298. https://doi.org/10.1016/j.intmar.2013.09.007 DOI: https://doi.org/10.1016/j.intmar.2013.09.007
Rodríguez-Rabadán, M., Caluori, R., & Romano, C. (2025). Impacto emocional del branded content. Visual Review, 17(6), 95–109. https://doi.org/10.62161/revvisual.v17.5949 DOI: https://doi.org/10.62161/revvisual.v17.5949
Rodríguez-Ulcuango, O. M., Guerra-Flores, C. O., Sánchez-Chávez, R. F., & Cedeño-Ávila, G. M. (2025). Sensorial marketing within consumer behavior. Cogent Business & Management, 12(1), 2503422. https://doi.org/10.1080/23311975.2025.2503422 DOI: https://doi.org/10.1080/23311975.2025.2503422
Scholz, C., Chan, H.-Y., & Falk, E. B. (2025). Brain activity explains message effectiveness: A mega-analysis of 16 neuroimaging studies. PNAS Nexus, 4(11), pgaf287. https://doi.org/10.1093/pnasnexus/pgaf287 DOI: https://doi.org/10.1093/pnasnexus/pgaf287
van Diepen, R. M., Boksem, M. A. S., & Smidts, A. (2025). Reliability of EEG metrics for assessing video advertisements. Journal of Advertising, 54(4), 506–526. https://doi.org/10.1080/00913367.2024.2418109 DOI: https://doi.org/10.1080/00913367.2024.2418109
Wang, G., Tian, L., Liu, J., Nie, S., & Yu, S. (2024). Neural mechanisms of cognitive load. Current Psychology, 43, 29316–29332. https://doi.org/10.1007/s12144-024-06577-2 DOI: https://doi.org/10.1007/s12144-024-06577-2
Xiao, L., Li, X., & Mou, J. (2026). Exploring user engagement behavior. Internet Research, 36(1), 154–188. https://doi.org/10.1108/INTR-07-2023-0521 DOI: https://doi.org/10.1108/INTR-07-2023-0521
Yan, R., & Hu, X. (2026). Understanding information sharing. Current Psychology, 45, 174. https://doi.org/10.1007/s12144-025-08586-1 DOI: https://doi.org/10.1007/s12144-025-08586-1
Yang, Q., Wang, Y., Wang, Q., Jiang, Y., & Li, J. (2025). Harmonizing sight and sound. Journal of Theoretical and Applied Electronic Commerce Research, 20(2), 69. https://doi.org/10.3390/jtaer20020069 DOI: https://doi.org/10.3390/jtaer20020069
Ye, C., Liu, R., Guo, L., Zhao, G., & Liu, Q. (2024). A negative emotional state impairs individuals’ ability to filter distractors from working memory: an ERP study. Cognitive, Affective & Behavioral Neuroscience, 24(3), 491–504. https://doi.org/10.3758/s13415-024-01166-z DOI: https://doi.org/10.3758/s13415-024-01166-z
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Authors retain copyright and transfer to the journal the right of first publication and publishing rights

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Those authors who publish in this journal accept the following terms:
-
Authors retain copyright.
-
Authors transfer to the journal the right of first publication. The journal also owns the publishing rights.
-
All published contents are governed by an Attribution-NoDerivatives 4.0 International License.
Access the informative version and legal text of the license. By virtue of this, third parties are allowed to use what is published as long as they mention the authorship of the work and the first publication in this journal. If you transform the material, you may not distribute the modified work. -
Authors may make other independent and additional contractual arrangements for non-exclusive distribution of the version of the article published in this journal (e.g., inclusion in an institutional repository or publication in a book) as long as they clearly indicate that the work was first published in this journal.
- Authors are allowed and recommended to publish their work on the Internet (for example on institutional and personal websites), following the publication of, and referencing the journal, as this could lead to constructive exchanges and a more extensive and quick circulation of published works (see The Effect of Open Access).








