Exploring Cognitive Response Trends in the Age of Social Media

Mariko Rizkiansyah, Dadang Sugiana, Asep Suryana, Ira Mirawati

Abstract


Researchers have studied cognitive responses since their emergence in the era of television and radio media. There is much research related to advertising. However, in today's era, social media is taking over the role of television and radio as popular media for publishing messages. This research explains the development trend of cognitive response research in the social media era and the pattern of topics used in this research related to cognitive response and social media. This research uses the Prisma method to determine the answer to this question. To make research more accessible, researchers also used Rayyan.AI and VostViewer for data screening. The results show many trends in cognitive response research and social media related to COVID-19. Generally, research links cognitive responses with trust in a product or issue. Most research also makes a connection between cognitive response and the participation of social media visitors. Additionally, there is plenty of research on test effect variation from the dimensions of cognitive theory of response to social media. Topics regarding advertising are still widely used for research; meanwhile, other themes relate to health communication, politics, and news. Although Cognitive response is a widely known theory, it still can be developed and improved to help solve problem regarding social media.

 

Keywords: Cognitive response, social media, VosViewer visualization, research trends, COVID-19.


https://doi.org/10.17576/JKMJC-2024-4002-29


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Aditiawarman, M. (2019). Hoax and hate speech in the middle world. Toggak Tuo.

Akram, M., Nasar, A., & Arshad-Ayaz, A. (2023). A systematic review for netizens' response to the truth manipulation on social media. Knowledge Management & e-Learning, 15(2), 322-342.

Belch, G. (1982). The effects of television commercial repetition on cognitive response and message acceptance. Journal of Consumer Research, 9(1), 56-65.

Belch, G. E. (1981). An examination of comparative and noncomparative television commercials: The effects of claim variation and repetition on cognitive response and message acceptance. Journal of Marketing Research, 18(3), 333-349.

Brucks, M., Armstrong, G. M., & Goldberg, M. E. (1988). Children's use of cognitive defenses against television advertising: A cognitive response approach. Journal of Consumer Research, 14(4), 471-482.

Buda, R., & Zhang, Y. (2000). Consumer product evaluation: the interactive effect of message framing, presentation order, and source credibility. Journal of Product & Brand Management, 9(4), 229-242.

Calder, B. (1978). Cognitive response, imagery, and scripts: What is the cognitive basis of attitude? Advances in Consumer Research, 5(1), 630-634.

Choi, M., Choi, Y., & Kim, D. Y. (2023). Digital natives: Internal defence mechanism to distrust tourism advertisements. Current Issues in Tourism, 26(16), 2692-2707.

Coursey, D. H. (1992). Information credibility and choosing policy alternatives: An experimental test of cognitive-response theory. Journal of Public Administration Research and Theory, 2(3), 315-331.

Dardis, F., Baumgartner, F., Amber E. Boydstun, Suzanna DeBoef, & Fuyuan Shen. (2008). Media framing of capital punishment and its impact on individuals' cognitive responses. Mass Communication & Society, 11(2), 115-140.

Dijck, J. (2013). The culture of connectivity: A critical history of social media. Oxford: Oxford University Press.

Fitri, S. (2017). Positive and negative impact of social media on children's social change. Naturalistic: Jurnal Kajian Penelitian Pendidikan dan Pembelajaran, 118-123.

Greenwald, A. G., Brock, T.C., & Ostrom, T. M. (2013). Psychological foundations of attitudes. Academic Press.

Han, K. S., & Lee, T. J. (2014). The impact of regulatory focus and message frame on consumers' responses to promotional campaigns on social networking sites (SNSs). International Journal of Applied Engineering Research, 9(22), 14835-14845.

Hynes, N., & Wilson, J. (2016). I do it, but don't tell anyone! Personal values, personal and social norms: Can social media play a role in changing pro-environmental behaviours? Technological Forecasting and Social Change, 111, 349-359.

Jeon, J. O., & Baeck, S. (2016). What drives consumer’s responses to brand crisis? The moderating roles of brand associations and brand-customer relationship strength. Journal of Product & Brand Management, 25(6), 550-567.

Johnson, D. S., Riley, B. K., & Sato, S. (2017). The adverse effect of doctors’ skepticism toward prescription drugs. International Journal of Pharmaceutical and Healthcare Marketing, 11(3), 222-234.

Jung, M., Lee, Y. L., Yoo, C. M., Kim, J. W., & Chung, J. E. (2018). Exploring the cognitive, affective, and behavioral responses of Korean consumers toward mobile payment services: A text mining approach. In Yamamoto, S., & Mori, H. (Eds.), Human interface and the management of information. Interaction, visualization, and analytics (Vol. 10904, pp. 624–642). HIMI 2018. Lecture Notes in Computer Science. Springer, Cham.

Kılıç, İ., Seçilmiş, C., & Özdemir, C. (2023). The role of travel influencers in volunteer tourism: an application of the cognitive response theory. Current Issues in Tourism, 27(2), 200-216.

Kim, A. J., & Johnson, K. K. (2016). Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook. Computers in Human. Behavior, 58, 98-108.

Koo, D. M. (2003). Inter‐relationships among store images, store satisfaction, and store loyalty among Koreadiscount retail patrons. Asia Pacific Journal of Marketing and Logistics, 15(4), 42-71.

Kurniawan, A. (2020, January 28). Understanding social media – History, function, role, types, characteristics, growth, impact, experts. Guru Pendidikan.co.id.

Lavidge, R. J., & Steiner, G. A. (1961). A model for predictive measurements of advertising effectiveness. Journal of Marketing, 25(6), 59-62.

Lee, C., & Lee, S. (2023). A study of users' EEG responses to different types of fashion films. Journal of the Korean Society of Clothing and Textiles, 47(2), 323-336.

Leng, H. K. (2013). Methodological issues in using data from social networking sites. Cyberpsychology, Behavior, and Social Networking, 16(9), 686-689.

Li, W., Gao, L., & Ke, Y. (2014). Social commerce: The critical role of argument strength and source dynamism of eWOM. PACIS 2014 Proceedings, 60.

Li, M. (2021). The synergistic effects of solutions journalism and corporate social responsibility advertising. Digital Journalism, 9(3), 336-363.

Lu, Y., Qiu, J., Jin, C., Gu, W., & Dou, S. (2022). The influence of psychological language words contained in microblogs on dissemination behaviour in emergency situations–Mediating effects of emotional responses. Behaviour & Information Technology, 41(6), 1337-1356.

Lu, X., Vijaykumar, S., Jin, Y., & Rogerson, D. (2022). Think before you Share: Beliefs and emotions that shaped COVID-19 (Mis) information vetting and sharing intentions among WhatsApp users in the United Kingdom. Telematics and Informatics, 67, 101750.

MacLeod, A. (2014). The impact of communication on human behaviour in times of crisis. Journal of Business Continuity & Emergency Planning, 8(2), 134–140.

Mandolfo, M., Baisi, F., & Lamberti, L. (2023). How did you feel during the navigation? Influence of emotions on browsing time and interaction frequency in immersive virtual environments. Behavior & Information Technology, 42(8), 1216-1229.

Meirick, P. (2002). Cognitive responses to negative and comparative political advertising. Journal of Advertising, 31(1), 49-62.

Moher, D., Cook, D. J., Eastwood, S., & Olkin, I. R. (1999). Improving the quality of reports of meta-analyses of randomized controlled trials: the QUOROM statement. The Lancet, 354(9193), 1896-1900.

Mohammed, M. T. S., Ibrahim, F., & Yunus, N. (2021). Exploring the relationship of social media usage and multitasking of social media on self-efficacy and academic performance. Jurnal Komunikasi: Malaysian Journal of Communication, 37(1), 227-243.

Myrick, J. G., & Willoughby, J. F. (2022). A mixed methods inquiry into the role of Tom Hanks’ COVID-19 social media disclosure in shaping willingness to engage in prevention behaviors. Health Communication, 37(7), 824-832.

Nagler, R. H., Vogel, R. I., Rothman, A. J., Yzer, M. C., & Gollust, S. E. (2023). Vulnerability to the effects of conflicting health information: Testing the moderating roles of trust in news media and research literacy. Health Education & Behavior, 50(2), 224-233.

Paek, H. J., Hove, T., & Jeon, J. (2013). Social media for message testing: A multilevel approach to linking favorable viewer responses with message, producer, and viewer influence on YouTube. Health Communication, 28(3), 226–236

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, 71.

Palda, K. S. (1966). The hypothesis of a hierarchy of effects: A partial evaluation. Journal of Marketing Research, 3(1), 13-24.

Pomering, A., & Johnson, L. W. (2009). Advertising corporate social responsibility initiatives to communicate corporate image: Inhibiting scepticism to enhance persuasion. Corporate Communications: An International Journal, 14(4), 420-439.

Rajagopal. (2006). Brand excellence: measuring the impact of advertising and brand personality on buying decisions. Measuring Business Excellence, 10(3), 56-65.

Rarasati, & Pradekso, T. (2019). The effect of exposure to news of marine animals dead due to plastic waste and the zero waste campaign on behavior to reduce the use of plastic bags. Online Interaction, 7(4), 295-304.

Ren, W., Zhu, X., & Hu, Y. (2022). Differential effects of traditional and social media use on COVID-19 preventive behaviors: The mediating role of risk and efficacy perceptions. Journal of Health Psychology, 27(8), 1861-1874.

Richmond, J. R., Edmonds, K. A., Rose, J. P., & Gratz, K. L. (2020). Examining the impact of online rejection among emerging adults with borderline personality pathology: Development of a novel online group chat social rejection paradigm. Personality Disorders: Theory, Research, and Treatment, 11(5), 301-311.

Rycker, A. D., & Jamal, F. U. A. (2023). Do social media and messaging aps influence loneliness? The case of young Malaysian higher education students during the COVID-19 pandemic. Jurnal Komunikasi: Malaysian Journal of Communication, 39(1), 1-20

Sajithra, K., & Patil, D. (2013). Social media – History and components. IOSR Journal of Business and Management (IOSR-JBM), 7(1), 69-74.

Sari, M. P., & Lubis, E. E. (2017). Fenomena penggunan media sosial instagram sebagai komunikasi pembelajaran agama Islam oleh mahasiswa Fisip Universitas Riau. Jurnal Online Mahasiswa, 4(2), 1-13.

Seçilmiş, C., Özdemir, C., & Kılıç, İ. (2022). How travel influencers affect visit intention? The roles of cognitive response, trust, COVID-19 fear and confidence in vaccine. Current Issues in Tourism, 25(17), 2789-2804.

Shen, L. (2010). The effect of message frame in anti-smoking public service announcements on cognitive response and attitude toward smoking. Health Communication, 25(1), 11-21.

Shin, S., & Ki, E.-J. (2021). Attribution and attributional processes of organizations’ environmental messages. International Journal of Market Research, 63(5), 576-596.

Smith, R. E., & Swinyard, W. R. (1988). Cognitive response to advertising and trial: Belief strength, belief confidence and product curiosity. Journal of Advertising, 17(3), 3-14.

Statista. (2024, February 2). Social media & user-generated content. https://www.statista.com/markets/424/topic/540/social-media-user-generated-content/#overview

Strauss, C. (1989). Who gets ahead? Cognitive response to heteroglossia in American Political Culture. American Ethnologist, 17(2), 312-328.

Su, N., Mariadoss, B. J., & Reynolds, D. (2019). Emotional and cognitive involvement of consumers with hotel brands on social networking sites. Journal of Hospitality and Tourism Insights, 2(4), 377-390.

Taprial, V., & Kanwar, P. (2012). Understanding social media. Ventus Publishing.

Tan, J. J., Firdaus, A., & Aksar, A. I. (2024). Social media for political information: A systematic literature review. Jurnal komunikasi: Malaysian Journal of Communication, 40(1), 77-98

Taylor-Carter, M., Doverspike, D., & Alexander,, R. (1995). Message effects on the perception of the fairness of gender-based affirmative action: A cognitive response theory-based analysis. Social Justice Research, 8, 285-303.

Tsai, C. J., & Shyr, W. J. (2022). Using the DEMATEL method to explore influencing factors for video communication and visual perceptions in social media. Sustainability, 14(22), 15164.

Turow, J. (2020). Media today: Mass communication in a converging world. New York: Routledge.

Vaala, S. E., Ritter, M. B., & Palakshappa, D. (2022). Framing effects on US adults’ reactions to COVID-19 public health messages: Moderating role of source trust. The American Behavioral Scientist, 00027642221124664.

Veggi, S., & Zara, G. (2022). Investigating sex offending representation among politicians through Twitter. The Journal of Forensic Psychiatry & Psychology, 34(1), 131–141

Vermeer, S., & van den Heijkant, L. (2023). Break a story: Examining the effects of Instagram stories from news accounts on adolescents’ political learning. Journalism Studies, 25(9), 1029-1052.

Voorveld, H. A., & van Noort, G. (2014). Social media in advertising campaigns: Examining the effects on perceived persuasive intent, campaign and brand responses. Journal of Creative Communications, 9(3), 253-268.

Wang, Y., Ahmed, S., & Ting Bee, A. (2023). Selective avoidance as a cognitive response: Examining the political use of social media and surveillance anxiety in avoidance behavior. Behavior & Information Technology, 3(3), 590-604.

Wu, J., Orr, M., Inoue, Y., & Chang, Y. (2023). Drivers of the perceived social impact of the Super Bowl: mediation and moderation analyses. International Journal of Sports Marketing and Sponsorship, 24(5), 837-852.

Yan, X., Shah, A. M., Zhai, L., Khan, S., & Shah, S. A. A. (2018). Impact of mobile electronic word of mouth (EWOM) on consumers purchase intentions in the fast-causal restaurant industry in Indonesia. Proceedings of the 51st Hawaii International Conference on System Sciences.

Yeomans, L. (2015). Engagement and empathy discourses in corporate communication: The case of “the science of engagement”. Romanian Journal of Communication and Public Relations, 17(3), 27-39.

Yuan, D., Lin, Z., Filieri, R., Liu, R., & Zheng, M. (2020). Managing the product-harm crisis in the digital era: The role of consumer online brand community engagement. Journal Of Business Research, 115, 38-47.

Zhu, Q., Skoric, M., & Shen, F. (2018). I shield myself from them: Selective avoidance on social media during political protests. In K. Koc-Michalska, & D. Lilleker (Eds.), Digital politics: Mobilization, engagement and participation (pp. 112-131). Routeldge.


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