Revisión teórico-cientifícia del marco conceptual de la emoción y el sentimiento y su aplicación al neuromarketing

  1. Núñez-Cansado, Marian
  2. López López, Aurora
  3. Vela Delfa, Cristina
Vivat Academia

ISSN: 1575-2844

Year of publication: 2021

Issue: 154

Type: Article

DOI: 10.15178/VA.2021.154.E1357 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

More publications in: Vivat Academia


In this article we try to address a diachronic bibliographical revision of the main theoretical contributions regarding the conceptual frame of emotion and feeling and its use in neuromarketing investigation. In the last years, scientific investigation programs are more prone to break the predominant paradigm in emotion theory, that identifies emotion and feeling, leaning towards definitions more accurate to the distinction of both concepts, proposing a differential and multifaceted perspective. Nonetheless, the analysis of specific literature over neuromarketing points that, in practice, both terms are confused. Consequently, we fall into a neurocentrism that ignores the role that feelings play in decision making. Most studies aim their results in merely physiologic and biological aspects, leaving behind relevant aspects that are the result of cognitive processes largely associated to cultural, social, and cognitive aspects of the subject. This circumstance may take away validity from the theoretical construct, as well as limit its predictive capacity or lessen its actual validity in the design of its investigations. In the current scientifical context, and regarding the bibliographical revision performed through this investigation, we consider the definition of a clear and unified conceptual frame to be crucial, so much as to avoid theoretical misunderstandings as to improve the design of the investigations that have been applied. We consider the investigation in neuromarketing entails a higher scientific accuracy, which implies the realization of more precise and coherent theorical interpretations of an updated conceptual frame. Only this way we will be able to overcome current limitations inherent to the application of mixed and integrated methodologies with which we measure and observe brain activity in the neuromarketing field.

Bibliographic References

  • Ahvenniemi H., Pennanen K., Knuuti A., Arvola A. & Viitanen K. (2018). Impact of infill development on prices of existing apartments in Finnish urban neighbourhoods. International Journal of strategic property management, 22 (3) 157-167.
  • Aiger, M., Palacín M. y Cornejo J. M. (2013). La señal electrodérmica mediante Sociograph: metodología para medir la actividad grupal. International Journal of Social Psychology, (28), 3.
  • Alamoodi A. H., Zaidan B. B., Albahri K. I. y Zaidan A. A. (2020). Sentiment analysis and its applications in fighting COVID-19 and infectious. Expert Systems With Applications, 114155.
  • Angulo Murillo, N. S. (2020). Modelo para el análisis de sentimientos del banco de encuestas con preguntas sobre coronavirus de la OMS empleando principios de minería de textos. Mikarimin, 31-39.
  • Arcila-Calderón C., Ortega-Mohedano F., Jiménez-Amores J. y Trullenque, S. (2017). Análisis Supervisado de sentimientos políticos en español, clasificación en tiempos real de Tweets basado en aprendizaje automático. el Profesional de la Investigación, 1699-2407.
  • Arnold, M. (1960). Emotion and Personality. Vol 1. Psychological Aspects. Columbia University Press.
  • Avinash T., Dikshant L. y Seema, S. (2018). Methods of Neuromarketing and Implication of the Frontal Theta Asymmetry induced due to musical stimulus as choice modeling. International Conference on Computational Intelligence and Data Science (ICCIDS 2018), 55-67. Gurgaon. India.
  • Azcarate, A., Hageloh, F., Sande, K. y Valenti, R. (2005). Automatic facial emotion recognición.
  • Baldeesh, G. y Senior, C. (2008). Examining the influence of fame in the presence of beauty : an electrodermal ‘neuromarketing’ study. Journal of Consumer Behaviour, (7), 4-5.
  • Bagozzi R., Gopinath, M., y Nyer, P. (1999). El papel de las emociones en el marketing. Revista de la Academia de Ciencias del Marketing., (27)2, 184-206.
  • Barret, L. (2018). Emotion fingerprints or emotion populations ? A meta-analytic inves-tigation of autonomic features of emotion categories. Psychological Bulletin, 144, 343–393.
  • Bastiaansen M., Straatman S., Driessen E., Mitas O. y Stekelenburg Lin Wang, L. (2018) My destination in your brain: A novel neuromarketing approach for evaluating the effectiveness of destination marketing. Journal of Destination Marketing & Management, 76-88.
  • Bisquerra, R. (2000). Educación emocional y bienestar. Ciss- Praxis.
  • Cabeza, R. y, Nyberg, L. (2000). Imaging cognition II: An empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience, 1-47.
  • Carlson N. R., Heth D. C., Miller, H., Donahoe, J. W., Buskist, W. y Martin N. G. (2007). Psychology: The Science of Behavior. Pearson.
  • Casado, C. y Colomo, R. (2006). Un breve recorrido por la concepción de las emociones en la filosofía occidental. A Parte Rei. Revista de filosofía, (47)1-10.
  • Chen, J., Ariki, Y. y Takiguchi, T. (2013). Robust facial expressions recognition using 3D average face and ameliorated Adaboost. 21st ACM International Conference on Multimedia. 661-664.
  • Clark-Polner, E., Johnson, T. y Barret, L. F. (2017). Multivoxel pattern analysis does not provide evidence to support the existence of basic emotions. Cerebral Cortex, 1944-1948.
  • Damasio, A. (2003). En busca de Spinoza. Ediciones Destino. S.A
  • Damasio, A. (2006). El error de Descartes. Crítica.
  • Díaz Ortíz, A. (2010). Teorías de las motivaciones. Innovación y experiencias educativas, 1-6.
  • Dixon, T. (2003). From Passions to emotions. The Creation of a Secular Psychological Category. Cambridge University Press.
  • Ekman, P. y Friesen W.V. (1971). Constants across the cultures in the face and emotion. Journal of Personality and Social Psychology, 124-129.
  • Ekman, P. y Oster, H. (1981). Facial expressions of emotion. Studies in Psychology, 2 :7, 115-144.
  • Ekman, P. (1992). An argument for basic emotions. Cognition & Emotion, 169-200.
  • Fernández, A., Dufey, M. y Mourgues, C. (2007). Expresión y reconocimiento de emociones: un punto de encuentro entre evolución, psicofisiología y neurociencias. Revista Chilena de Neuropsicología, (2) 1, 8-20.
  • Fernández-Dols, J. M y Ruiz- Belda, M. A. (1995) ¿Son las sonrisas un signo de felicidad ? Revista de Personalidad y Psicología Social. (6), 113-119
  • García Andrade, A. (2019). Neurociencia de las emociones: la sociedad vista desde el individuo. Una aproximación a la vinculación sociología-neurociencia. Sociología, 39-71.
  • García, K. y Bertón L. (2021). Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA. Applied Soft Computing, (101) 10757.
  • Gaur S., Herjanto H. y Makkar M. (2014). Reviewofemotionsresearchinmarketing, 2002–2013. Journal of Retailing and Consumer Services, 917-923. Gill, R. y Singh, J. (2020). Study of neuromarketing techniques for proposing cost effective information driven framework for decision making. Materials Today: Proceedings.
  • Golnar-Nick, P., Farashi S. y Safari M. S. (2019). The application of EEG power for the predictión an interpretación of consumer decisión-making: a neuromarketing study. Physiology & Behavior, 90-98.
  • González, B. I. (2017). "En busca de Spinoza", de Antonio Damasio. Culturasmas:
  • Groeppel-Klein, A. (2005). Arousal and consumer in store behavior. Brain Research Bulletin, 428-437.
  • Hajcak G., Weinberg A., MacNamara A. y Foti D. (2012). ERPs and the study of emotion. Oxford University Press.
  • Hakim, A., Klorfeld, S., Sela, T., Friedman, D. y Shabat-Simon, M. (2019). Machines learn neuromarketing: Improving preference. International Journal of Research in Marketing.
  • Hamelin, N., Moujahid, O. y Thaichon O. (2017). Emotion and advertising effectiveness: A novel facial expression analysis approach. Journal of Retailing and Consumer Services, 36, 103-111.
  • Hamilton, W. L., Clark, K., Leskovec, J. y Jurafsky, D. (2016). Conference on empirical methods in natural language processing. Classification of domain-specific feelings by merging knowledge of feelings from multiple sources. 595-605.
  • Henriquez Miranda, C. G. (2016). Minería de Opiniones basado en la adaptación al español. Procesamiento del lenguaje natural, 25-32.
  • Hsu, L. y Chen Y. J. (2020). Neuromarketing, subliminal advertising, and hotel selection: An EEG study. Australasian Marketing Journal, 200-208.
  • James, W. (1985). ¿What is an emotion? Studies in Psychology, (6)21, 57-73.
  • Kleinginna, J. K y Kleinginna, N. (1981). A categorized list of emotion definitions, with suggestions for a consensual definition. Motivation and Emotion, 345-379.
  • Kumar, S., Yadava, M. y Roy, P. (2019). Fusion of EEG response and sentiment analysis of products review to predict customer satisfaction. Information Fusion, 52, 41-52. Kumar, S. Y. (2019). Fusion of EEG response and sentiment analysis of products review to predict customer satisfaction. Information Fusion, 52, 41-52.
  • LeDoux, J. (1996). The emotional brain: The mysterious underpinnings of emotional life. Simon & Schuster.
  • LeDoux, J. (2002). Synaptic Self: How Our Brains Become. Viking Books.
  • Lei Z., Yang Y. y Yang M. (2018). SAAN: una red de atención consciente del sentimiento para análisis de los sentimientos. SIGIR'18. 1197-1200. Arbor, USA.
  • Lewinski, P., Fransen, M. L. y Tan E. S. H. (2014). Predicting advertising effectiveness by facial expressions in response to amusing persuasive stimuli. ournal of Neuroscience, Psychology, & Economics, 7 (1), 1-14 .
  • Lim, M. (2018). Demystifying neuromarketing. Journal of Business Research, 105-220.
  • Lindquist, K. A., Wager, T. D., Kober, H., Bliss-Moreau, E. y Barrett, L. F. (2012). The brain basis of emotion: A meta-analytic review. Behavioural & Brain Sciencies, 35 (3), 121-143.
  • Magnone, P. (2012). La alegoría del carro del alma en Platón y en la Kaṭha Upaniṣad. Exégesis y hermenéutica de obras tardoantiguas y medievales, 87-127.
  • Mahamud, K. (2018). Emociones y sentimientos: coordenadas históricas y multidicisplinares de un campo de estudios claves para la ciencia de la educación. Avances en supervisión educativa. Revistas de la asociación de inspectores de España., 1-18.
  • Mandler, G. (1975). The search of emotion. En L. Levi, Emotions: Their Parameters and Measurement. (121-148). Raven Press.
  • Marañón, G. a. (1920). La Emoción. Voluntad, vol. IX.
  • Marañón, G. b. (1920). La reacción emotiva a la adrenalina. La Medicina Íbera.
  • Martínez Herrador, J. L., Núñez-Cansado M. y Vadunquillo M. I. (2020). Metodología de neuromarketing: medición de Sociograph aplicada al análisis de la narrativa audiovisual erótica y sus aplicaciones a la estrategia de mercadotecnia. Vivat Academia, (150), 131-153.
  • Melamed, A. (2016). Las teorías de las emociones y su relación con la cognición: un análisis desde la filosofía de la mente. Cuadernos de la facultad de humanidades y Ciencias Sociales. 49, 3-38. Morín, C. (2011). Neuromarketing: The New Science of Consumer Behavior. Society, 131-135.
  • Neethu, R. y Rajasree, M. S. (2013). The 4th international conference on computing, communications and networking technologies. Sentiment analysis in twitter using machine learning techniques, 1-5. Tiruchengode. / ICCCNT.2013.6726818
  • Núñez-Cansado, M., López López, A., & Caldevilla Domínguez, D. (2020). Situation of Neuromarketing Consulting in Spain. Frontiers in Psychology, 11, 1854.
  • Olofsson J. K., Nordin S., Sequeira H. y Polich J. (2008). Affective picture processing: An integrative review of ERP findings. Biological Psychology, 247-265.
  • Thorson E. y Heide M. P. (1990). The memory impact of commercials varying in emotional appeal and product involvement. Emotion in Advertising. Quorum Books.
  • Pang L. y Lee B. (2004). A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts. Proceedings of the 42nd ACL. 271--278.
  • Papez, J. (1995). A proposed mechanism of emotion. 1937. Journal Neuropsychiatry Clinic, 7(1), 103-12.
  • Plassmann, H., O'Doherty, J., Shiv, B. y Rangel, A. (2008). Marketing actions can modulate neural representations of experienced pleasantness. National Institutes of Health, 1050-1054.
  • Plutchik, R., & Ax, A. F. (1967). A critique of determinants of emotional state by schachter and singer (1962). Psychophysiology, 4(1), 79-82.
  • Poels, K. y Dewitte, S. (2006). How to capture the heart? Reviewing 20 years of emotion measurement in advertising. journal advertising research, 46, 18-37.
  • Rampl, L. V., Opitz, I. M., Welpe, I. M. y Kenning, P. (2016). The role of emotions in decision-making on employer brands: insights from functional magnetic. Springer Science+Business Media, 361-374.
  • Romero Moreno, F., Sanchez Martelo, C., Corredor B. Sánchez Cifuentes, F. y Ospina López, J. (2020). Análisis de sentimiento a las opiniones generadas. Risti, 187-203.
  • Ruanguttamanun, C. (2014). Neuromarketing: I put myself into a fMRI scanner and realized that I love Louis Vuitton ads. Procedia Social and Behavioral Sciencie, 211-218.
  • Russell, J. (1980). A circumplex model of affect. Journal Personal Sociology Psychology, 1161-1178.
  • Salah, A., Sebe, N. y Gevers, T. (2009). Communication and automatic interpretation of affect from facial expressions. En D. &. Gokay, Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific perspectives 157-183. Hershey (USA): IGI Global.
  • Scarantino, A. (2018). Are LeDoux´s suvirval circuits basic emotions under a diferente name? Behavioral Sciencies, 24, 75-82.
  • Scheutz, M. (2000). Surviving in a hostile multi-agent environment: how simple affective states can aid in the competition for resources. Proceedings of the Thirteenth Canadian Conference on Artificial Intelligence. 389-399. Montreal. Canada.
  • Shapiro, A., Sudhof, M. y Wilson, D. (2020). Measuring news sentiment. Journal of Econometrics.
  • Sherer, K. (1884). Aproaches of emotion. Psychology press. Taylor & Francis Group.
  • Souza Baelar, L. (2011). Estudio de las emociones: una perspectiva transversal. Contribuciones a las Ciencias Sociales, 16-32.
  • Sun Y., Wang Z., Zhang B., Zhao W., Xu f., Liu J. y Wang B. (2020). Residents sentiments towards electricity price policy: Evidence from text mining in social media. Conservation and Recycling, (160). 104903.
  • Trueba, C. (2009). La Teoría aristotélica de las emociones. Signos filosóficos, 1665-1324.
  • Vargas, A. y Espinoza, A. (2008). Pasión y Razón en Thomas Hobbes. Alpha. 26, 135-152.
  • Vecchiato, G., Cherubino, P., Maglione, A. G., Ezquierro, M. T. H., Marinozzi, F., Bini, F., Trettel, A. y Babiloni, F. (2014). How to measure cerebral correlates of emotions in marketing relevant tasks. Cognitive Computation, 6(4), 856–871.
  • Vigotsky, L. (2004). Teoría de las emociones: Estudio histórico- Psicológico. Akal Universitaria.
  • Wahab, W., Ridwan, M. y Kusumoputro, B. (2015). Design and implementation of an automatic face-image data acquisition system using IP based multi camera. International Journal Techonology, 1042-1049.
  • Wilson, T. W. J. (2005). Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language. Recognizing contextual polarity in phrase-level sentiment analysis. 347-354.
  • Yao, F. y Wang, Y. (2020). Domain-specific sentiment analysis for tweets during hurricanes (DSSA-H): A domain-adversarial neural-network-based approach. Computers, Environment and Urban Systems, 101522.
  • Zurawicki, L. (2010). Neuromarketing: Exploring the brain of the consumer. Heidelberg: Springer.