Czasopismo
Tytuł artykułu
Warianty tytułu
Języki publikacji
Abstrakty
The article aimed to examine the relationship between Generation Z's interactions on social networking sites in the context of herd behaviour and behavioural mimicry through central and peripheral content processing pathways. The study was conducted using the CAWI method on a group of 142 representatives of Generation Z from selected universities in Poland. Nonparametric tests were used for statistical analyses. In the case of information overload, approximately 20 % of respondents' interactions on different social media platforms may result from behavioural mimicry and herd behaviours. This type of activity is influenced primarily by the observed number of interactions and the emotional nature of other users' reactions. The observed differences are determined by gender, the type of social media platform, and related content specificity. Research limitations result from the specificity of the research sample in the context of its homogeneity and size. The theoretical contribution is related to the development of the cognitive-emotional-behavioural theory of memes about the imitation of interactions of social media users' conditioned herd behaviour and behavioural mimicry. The novelty of the research lies in the application of the theoretical Elaboration Likelihood Model approach to the analysis of herd behaviour and behavioural mimicry in the context of research on the cognitive, emotional, and behavioural activities of various social media platform users. (original abstract)
Rocznik
Numer
Strony
21-33
Opis fizyczny
Twórcy
autor
- Bialystok University of Technology
autor
- Cardiff Metropolitan University, United Kingdom; Curtin University, Australia; Toronto Metropolitan University, Canada
autor
- Kozminski University, Warsaw
autor
- A Coruña University, Spain
Bibliografia
- Ahmad, S. (2023). Social Media and Herd Mentality. Online content activates brain circuitry in ways you need to understand. Psychology Today (updated 8 September 2023). Retrieved from https://www.psychologytoday.com/us/blog/balanced/202309/social-media-and-herd-mentality
- Bamakan, S.M.H., Nurgaliev, I., & Qu, Q. (2019). Opinion leader detection: A methodological review, Expert Systems with Applications, 115, 200-222. doi: 10.1016/j.eswa.2018.07.069
- Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3, 265-299. doi: 10.1207/S1532785XMEP0303_03
- Bandura, A., & McClelland, D.C. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall. Prentice-Hall.
- Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS quarterly, 805-825. doi: 10.2307/25148755
- Cao, J., Liu, F., Shang, M., & Zhou, X. (2021). Toward street vending in post COVID-19 China: Social networking services information overload and switching intention. Technology in Society, 66, 101669. doi: 10.1016/j.techsoc.2021.101669
- Casaló L.V., Flavián C., & Ibáñez-Sánchez S. (2018). Influencers on Instagram: Antecedents and consequences of opinion leadership. Journal of Business Research, 92, 168-178. doi: 10.1016/j.jbusres.2018.07.005
- Chang, H.H., Lu, Y.Y., & Lin, S.C. (2020). An elaboration likelihood model of consumer respond action to Facebook second-hand marketplace: Impulsiveness as a moderator. Information & Management, 57(2), 103171. doi: 10.1016/j.im.2019.103171
- Charlesworth, A. (2012). Internet Marketing: A Practical Approach. Routledge, New York, p 290.
- Chartrand, T.L., & Bargh, J.A. (1999). The chameleon effect: The perception-behavior link and social interaction. Journal of Personality and Social Psychology, 76(6), 893-910. doi: 10.1037/0022-3514.76.6.893
- Chung, C.H., Chiu, D.K.W., Ho, K.K.W., & Au, C.H. (2020). Applying social media to environmental education: is it more impactful than traditional media? Information Discovery and Delivery, 48(4), 255-266. doi: 10.1108/IDD-04-2020-0047
- Cialdini, R.B., Kallgren, C.A., & Reno, R.R. (1991). A Focus Theory of Normative Conduct: A Theoretical Refinement and Reevaluation of the Role of Norms in Human Behavior. In M.P. Zanna, (Ed.), Advances in Experimental Social Psychology, 24, (pp. 201-234), Academic Press. doi: 10.1016/S0065-2601(08)60330-5
- Conte, R. (2000). Memes through (social) minds. In R. Aunger (Ed.), Darwinizing culture: The status of memetics as a science (pp. 83-120). Oxford, England: Oxford University Press. doi: 10.1093/acprof:oso/9780192632449.001.0001
- Cracco E., Genschow O., Radkova I., & Brass M. (2018). Automatic imitation of pro- and antisocial gestures: Is implicit social behavior censored? Cognition, 170, 179-189. doi: 10.1016/j.cognition.2017.09.019"10.1016/j.cognition.2017.09.019
- Davies, B., Turner, M., & Udell, J. (2023). It helps to be funny or compassionate: An exploration of user experiences and evaluation of social media micro-intervention designs for protecting body image. Computers in Human Behavior, 150, 107999. doi: 10.1016/j.chb.2023.107999
- Dawkins, R. (1976). The Selfish Gene. Oxford: Oxford University Press.
- Distin, K. (2014). Foreword to the Chinese translation of The Selfish Meme. Cambridge University Press and Beijing World Publishing. Retrieved from http://www.distin.co.uk/memes/scans/Foreword_Chinese.pdf
- Fasya, E.L., van den Bos, E., Heylen, D.K.J., & Kret, M.E. (2024). Smile mimicry smoothens human-virtual human interactions. International Journal of Human-Computer Studies, 183, 103182. doi: 10.1016/j.ijhcs.2023.103182
- Fatt, S.J., & Fardouly, J. (2023). Digital social evaluation: Relationships between receiving likes, comments, and follows on social media and adolescents' body image concerns. Body Image, 47, 101621. doi: 10.1016/j.bodyim.2023.101621
- Firth, J., Torous, J., Stubbs, B., Firth, J.A., Steiner, G.Z., Smith, L., Alvarez-Jimenez, M., Gleeson, J., Vancampfort, D., Armitage, C.J., & Sarris. J. (2019). The "online brain": how the Internet may be changing our cognition. World Psychiatry, 18(2),119-129. doi: 10.1002/wps.20617
- Fleck, N.D., & Quester, P. (2007). Birds of a feather flock together... definition, role and measure of congruence: An application to sponsorship. Psychology & Marketing, 24(11), 975-1000. doi: 10.1002/mar.20192
- Flores, P.M., Hilbert, M. (2023). Lean-back and lean-forward online behaviors: The role of emotions in passive versus proactive information diffusion of social media content. Computers in Human Behavior, 147,107841. doi: 10.1016/j.chb.2023.107841
- Fu, J.R., Ju, P.H., & Hsu, C.W. (2015). Understanding why consumers engage in electronic word-of-mouth communication: Perspectives from the theory of planned behavior and justice theory. Electronic Commerce Research and Applications, 14(6), 616-630. doi: 10.1016/j.elerap.2015.09.003
- George, D., & Mallery, P. (2016). IBM SPSS statistics 23 step by step: A simple guide and reference. New York Routledge.
- Geyser W. (2022). What is an influencer? Social media influencers defined [updated February 14th, 2024]. Influencer Marketing Hub. Retrieved from https://influencermarketinghub.com/what-is-an-influencer
- Graczyk-Kucharska, M., & Erickson, G.S. (2020). A person-organization fit model of Generation Z: Preliminary studies. Journal of Entrepreneur-ship, Management and Innovation, 16(4), 149-176. doi: 10.7341/20201645
- Harrigan, N., Achananuparp, P., & Lim, E.P. (2012). Influentials, novelty, and social contagion: The viral power of average friends, close communities, and old news. Social Networks, 34(4), 470-480. doi: 10.1016/j.socnet.2012.02.005
- Hatfield, E., Rapson, R.L., & Le, Y.-C.L. (2009). Emotional contagion and empathy. In J. Decety & W. Ickes (Eds.), The social neuroscience of empathy (pp. 19-30). Boston Review. doi: 10.7551/mit-press/9780262012973.003.0003
- Haug, M., Reiter, J., & Gewald, H. (2024). Content creators on Instagram - How users cope with stress on social media. Telematics and Informatics Reports, 13, 100111. doi: 10.1016/j.teler.2023.100111
- Haug, M., Reiter, J., & Gewald, H. (2024). Content creators on Instagram - How users cope with stress on social media. Telematics and Informatics Reports, 13, 100111. doi: 10.1016/j.teler.2023.100111
- Hayes, R.A., Carr, C.T., & Wohn, D.Y. (2016). One click, many meanings: Interpreting paralinguistic digital affordances in social media. Journal of Broadcasting & Electronic Media, 60(1), 171-187. doi: 10.1080/08838151.2015.1127248
- Herman, L.E., Udayana, I.B.N., & Farida, N. (2021). Young generation and environmental friendly awareness: does it the impact of green advertising?. Business: Theory and Practice, 22(1), 159-166. doi: 10.3846/btp.2021.12417
- Jacoby, J., Speller, D.E., & Kohn, C.A. (1974). Brand Choice Behavior as a Function of Information Load. Journal of Marketing Research, 11(1), 63-69. doi: 10.1177/002224377401100106
- Karr-Wisniewski, P. & Lu, Y. (2010). When more is too much: Operationalizing technology overload and exploring its impact on knowledge worker productivity, Computers in Human Behavior, 26(5), 1061-1072. doi: 10.1016/j.chb.2010.03.008
- Katz, E., & Lazarsfeld, P.F. (1955). Personal influence: the part played by people in the flow of mass communications. Free Press.
- Kohli, C., Suri, R., & Kapoor, A. (2014). Will social media kill branding? Business Horizons, 58(1), 35-44. doi: 10.1016/j.bushor.2014.08.004
- Kowalczyk-Purol, K. (2015). Memes and cognitive schemas. Bridging the gap between memetics and social sciences. Teksty z Ulicy. Zeszyt Memetyczny, 16, 27-41.
- Krippes, M., Najmaei, M., & Wach, K. (2024). The impact of sustainable product attributes on the consumer behaviour of Generation Z in Germany. Polish Journal of Management Studies, 29(2), 346-364. doi: 10.17512/pjms.2024.29.2.18.
- Laninga-Wijnen, L., & Veenstra, R. (2023). Peer similarity in adolescent social networks: Types of selection and influence, and factors contributing to openness to peer influence. In B. Halpern-Felsher (Ed.), Encyclopedia of Child and Adolescent Health (1st Edition, pp. 196-206), Academic Press. doi: 10.1016/B978-0-12-818872-9.00047-9
- Laurn, S. (2023). 7 Types of Social Media Interactions (and How To Handle Them). Retrieved from https://blog.hootsuite.com/social-media-interaction/
- Levickaitė, R. (2010). Generations X, Y, Z: how social networks form the concept of the world without borders (the case of Lithuania). Creativity Studies, 3(2), 170-183. doi: 10.3846/limes.2010.17
- Luo, L., Liu, J., Shen, H., Lai, Y. (2023). Vote or not? How language mimicry affect peer recognition in an online social Q&A community. Neurocomputing, 530, 139-149. doi: 10.1016/j.neucom.2023.01.086
- Mattke, J., Maier, Ch., Reis, L., & Weitzel, T. (2020). Herd behavior in social media: The role of Facebook likes, strength of ties, and expertise. Information & Management, 57(8), 103370. doi: 10.1016/j.im.2020.103370
- Matyjek, M., Meliss, S., Dziobek, I., & Murayama, K. (2020). A Multidimensional View on Social and Non-Social Rewards. Frontiers in Psychiatry, 11, 818. doi: 10.3389/fpsyt.2020.00818
- Menczer, F. & Hill, T. (2020). The Attention Economy. Scientific American Magazine, 323(6), 54. doi: 10.1038/scientificamerican1220-54
- Menczer, F., & Hills, T. (2020). The Attention Economy. Scientific American, 323(6), 54-61. doi: 10.1038/scientificamerican1220-54
- Modgil, S., Singh, R.K., Gupta, S., & Donnehy, D. (2021). A Confirmation Bias View on Social Media Induced Polarisation During Covid-19. Information Systems Frontiers, 26, 417-441. doi: 10.1007/s10796-021-10222-9
- Moradi, M., & Zihagh, F. (2022). A meta-analysis of the elaboration likelihood model in the electronic word of mouth literature. International Journal of Consumer Studies, 46(5), 1900-1918. doi: 10.1111/ijcs.12814
- Müller, J., & Christandl, F. (2019). Content is king - But who is the king of kings? The effect of content marketing, sponsored content & user-generated content on brand responses. Computers in Human Behavior, 96, 46-55. doi: 10.1016/j.chb.2019.02.006
- Muntinga, D.G. (2013). Catching COBRAs. Amsterdam: SWOCC.
- Park, S., & Jung, J. (2023). The interplay between social media virality metrics and message framing in influence perception of pro-environmental messages and behavioral intentions. Telematics and Informatics, 78, 101947. doi: 10.1016/j.tele.2023.101947
- Petty, R.E. & Cacioppo, J.T. (1986) The Elaboration Likelihood Model of Persuasion. Advances in Experimental Social Psychology, 19, 123-205. doi: 10.1016/S0065-2601(08)60214-2
- Ruvio, A., Gavish, Y., & Shoham, A. (2013). Consumer's doppelganger: A role model perspective on intentional consumer mimicry. Journal of Consumer Behaviour, 12(1), 60-69. doi: 10.1002/cb.1415
- Sasahara, K., Chen, W., Peng, H., Ciampaglia, G.L., Flammini, A., & Menczer, F. (2021). Social influence and unfollowing accelerate the emergence of echo chambers. Journal of Computational Social Science, 4(1), 381-402. doi: 10.48550/arXiv.1905.03919
- Schlaile, M.P., Knausberg, T., Mueller, M., & Zeman, J. (2018). Viral ice buckets: A memetic perspective on the ALS Ice Bucket Challenge's diffusion. Cognitive Systems Research, 52, 947-969. doi: 10.1016/j.cogsys.2018.09.012
- Sheng, N., Yang, Ch., Han, L., & Jou, M. (2023). Too much overload and concerns: Antecedents of social media fatigue and the mediating role of emotional exhaustion. Computers in Human Behavior, 139, 107500. doi: 10.1016/j.chb.2022.107500
- Smeijers, D., Uzieblo, K., Glennon, J.C., Driessen J.M.A, & Brazil, I.A. (2022). Examining Individual Differences in Social Reward Valuation: a Person-Based Approach. Journal of Psychopathology and Behavioral Assessment, 44, 312-325. doi: 10.1007/s10862-021-09934-8
- Smith, K. (2017). Mobile advertising to Digital Natives: preferences on content, style, personalization, and functionality. Journal of Strategic Marketing, 27, 1-14. doi: 10.1080/0965254X.2017.1384043
- Song, Y., Lin, Q., Kwon, K.H., Choy, Ch. H.Y., Xu, R. (2022). Contagion of offensive speech online: An interactional analysis of political swearing. Computers in Human Behavior, 127, 107046. doi: 10.1016/j.chb.2021.107046
- Stavrositu, C.D., & Kim, J. (2014). Social media metrics: Third-person perceptions of health information. Computers in Human Behavior, 35, 61-67. doi: 10.1016/j.chb.2014.02.025
- Stel, M., & Vonk, R. (2010). Mimicry in social interaction: Benefits for mimickers, mimickees, and their interaction. British Journal of Psychology, 101(2), 311-323. doi: 10.1348/000712609x465424
- Strong, E. (1925). The Psychology of Selling. MacGraw-Hill, Nueva York.
- Sun, H. (2013). A Longitudinal Study of Herd Behavior in the Adoption and Continued Use of Technology. MIS Quarterly, 37(4), 1013-1041. http://www.jstor.org/stable/43825780
- Sun, H., Feng, Y., & Meng, Q. (2024). Information dissemination behavior of self-media in emergency: Considering the impact of information synergistic-hedging effect on public utility. Expert Systems with Applications (In Press, Journal Pre-proof), 124110. doi: 10.1016/j.eswa.2024.124110
- Tan, X., & Cousins, K.C. (2016). Herding Behavior in Social Media Networks in China. Americas Conference on Information Systems. Retrieved from https://core.ac.uk/download/pdf/301368818.pdf
- Trinity College Dublin (2024). Frequently asked questions. Trinity College Dublin School of Linguistic, Speech and Communication Sciences Research Ethics Committee. Retrieved from www.tcd.ie/slscs/assets/documents/research/ethics/SLSCS_REC_FAQs.pdf.
- Vandenbosch, L., Fardouly, J., & Tiggemann, M. (2022). Social media and body image: Recent trends and future directions. Current Opinion in Psychology, 45, 101289. doi: 10.1016/j.copsyc.2021.12.002
- Whelan, G., Moon, J., & Grant, B. (2013). Corporations and Citizenship Arenas in the Age of Social Media. Journal of Business Ethics, 118(4), 777-790. doi: 10.1007/s10551-013-1960-3
- Wohn, D.Y., Carr, C.T., & Hayes, R.A. (2016). How affective is a "Like"?: The effect of paralinguistic digital affordances on perceived social support. Cyberpsychology, Behavior, and Social Networking, 19(9), 562-566. doi: 10.1089/cyber.2016.0162
- Xiao, C., Ye, J., Esteves, R.M., & Rong, C. (2016). Using Spearman's correlation coefficients for exploratory data analysis on big dataset. Concurrency and Computation: Practice and Experience, 28, 3866-3878. doi: 10.1002/cpe.3745"10.1002/cpe.3745
- Xu, F., & Warkentin, M. (2020). Integrating elaboration likelihood model and herd theory in information security message persuasiveness. Computers & Security, 98, 102009. doi: 10.1016/j.cose.2020.102009
- Xu, M., Wei, Z., & Wu, J. (2022). How emotional communication happens in social media: Predicting "Arousal-Homophily-Echo" emotional communication with multi-dimensional features. Telematics and Informatics Reports, 8, 100019. doi: 10.1016/j.teler.2022.100019
- Zha, X., Yang, H., Yan, Y., Liu, K., & Huang, Ch. (2018). Exploring the effect of social media information quality, source credibility and reputation on informational fit-to-task: Moderating role of focused immersion. Computers in Human Behavior, 79, 227-237. doi: 10.1016/j.chb.2017.10.038
- Zhang, S., Zhang, Y., Li, J., Ni, Z., & Liu, Z. (2024). Heart or mind? The impact of congruence on the persuasiveness of cognitive versus affective appeals in debunking messages on social media during public health crises. Computers in Human Behavior, 154, 108136. doi: 10.1016/j.chb.2024.108136
- Zhang, S., Zhao, L., Lu, Y. & Yang, J. (2016). Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services. Information & Management, 53(7), 904-914. doi: 10.1016/j.im.2016.03.006
- Zhang, X., & Ghorbani, A.A. (2020). An overview of online fake news: Characterization, detection, and discussion. Information Processing & Management, 57(2), 102025. doi: 10.1016/j.ipm.2019.03.004
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171702738