Abstract
Experiencing antisocial online behaviour such as cyberbullying and internet trolling is associated with a range of negative psychological and physical outcomes. To understand why people are motivated to engage in antisocial online behaviour, researchers have explored a variety of individual differences including traits, motivations, and cognitions. In the current study, we adopted developmental frameworks to explore antisocial use of social media across different age cohorts. Participants (N = 665, 51% female) with an average age of 28 years (SD = 8.86) completed an online questionnaire assessing antisocial use of social media. Adopting previous guidelines, participants were categorised as emerging adults (aged 18–25 years; 50%), adults (aged 26–44 years; 42%), and middle age (aged 45–59 years; 8%). A one-way ANOVA showed a statistically significant effect of age cohort on antisocial use; however, contrary to expectations, adults reported higher antisocial use of social media compared to emerging adults and middle-aged adults. There was no statistically significant difference between emerging adults and middle-aged adults. Results are discussed through the lens of Erikson’s psychosocial theory and Social Convoy Model and recommendations are provided to manage and prevent perpetration of antisocial online behaviour.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alhabash, S., & Ma, M. (2017). A tale of four platforms: Motivations and uses of Facebook, Twitter, Instagram, and Snapchat among college students? Social Media + Society, 3(1), 205630511769154. https://doi.org/10.1177/2056305117691544
Antonucci, T. C., Ajrouch, K. J., & Birditt, K. S. (2014). The convoy model: Explaining social relations from a multidisciplinary perspective. The Gerontologist, 54(1), 82–92. https://doi.org/10.1093/geront/gnt118
Barker, V. (2012). A generational comparison of social networking site use: The influence of age and social identity. The International Journal of Aging and Human Development, 74(2), 163–187. https://doi.org/10.2190%2FAG.74.2.d
Barnhart, B. (2021, March 9). Social media demographics to inform your brand’s strategy in 2021. Sprout Social. https://sproutsocial.com/insights/new-social-media-demographics/
Bartlett, C. P., & Chamberlin, K. (2017). Examining cyberbullying across the lifespan. Computers in Human Behavior, 71, 444–449. https://doi.org/10.1016/j.chb.2017.02.009
Cho, Y. K., & Yoo, J. W. (2017). Cyberbullying, internet and SNS usage types, and perceived social support: A comparison of different age groups. Information, Communication & Society, 20(10), 1464–1481. https://doi.org/10.1080/1369118X.2016.1228998
Craker, N., & March, E. (2016). The dark side of Facebook®: The Dark Tetrad, negative social potency, and trolling behaviours. Personality and Individual Differences, 102, 79–84. https://doi.org/10.1016/j.paid.2016.06.043
Erikson, E. H. (1959). Identity and the life cycle: Selected papers. International Universities Press.
Facebook (2022). Put a stop to bullying. Retrieved March 1, 2020, from https://www.facebook.com/safety/bullying
Ferenczi, N., Marshall, T. C., & Bejanyan, K. (2017). Are sex differences in antisocial and prosocial Facebook use explained by narcissism and relational self-construal? Computers in Human Behavior, 77, 25–31. https://doi.org/10.1016/j.chb.2017.08.033
Geary, C., March, E., & Grieve, R. (2021). Insta-identity: Dark personality traits as predictors of authentic self-presentation on Instagram. Telematics and Informatics, 63, 101669. https://doi.org/10.1016/j.tele.2021.101669
Gibb, Z. G., & Devereux, P. G. (2014). Who does that anyway? Predictors and personality correlates of cyberbullying in college. Computers in Human Behavior, 38, 8–16. https://doi.org/10.1016/j.chb.2014.05.009
Hinduja, S., & Patchin, J. W. (2014). Bullying beyond the schoolyard: Preventing and responding to cyberbullying. Corwin Press.
Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook. Upper Saddle River.
Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin, 140(4), 1073. https://doi.org/10.1037/a0035618
Levitt, M. J., Guacci, N., & Levitt, J. L. (1993). Convoys of social support in childhood and early adolescence: Structure and function. Developmental Psychology, 29(5), 811–818. https://doi.org/10.1037/0012-1649.29.5.811
Malone, J. C., Liu, S. R., Vaillant, G. E., Rentz, D. M., & Waldinger, R. J. (2016). Midlife Eriksonian psychosocial development: Setting the stage for late-life cognitive and emotional health. Developmental Psychology, 52(3), 496–508. https://doi.org/10.1037/a0039875
March, E., & Marrington, J. Z. (2021). Antisocial and prosocial online behaviour: Exploring the roles of the dark and light triads. Current Psychology, 1–4. https://doi.org/10.1007/s12144-021-01552-7
March, E., & Steele, G. (2020). High esteem and hurting others online: Trait sadism moderates the relationship between selfesteem and Internet trolling. Cyberpsychology, Behavior, and Social Networking, 23(7), 441–446. https://doi.org/10.1089/cyber.2019.0652
Marcia, J. E., Waterman, A. S., Matteson, D. R., Archer, S. L., & Orlofsky, J. L. (2012). Ego identity: A handbook for psychosocial research. Springer Science & Business Media
Newman, B. M., & Newman, P. R. (2017). Development through life: A psychosocial approach. Cengage Learning.
Patchin, J. W., & Hinduja, S. (2012). Cyberbullying: An update and synthesis of the research. In J. W. Patchin & S. Hinduja (Eds.), Cyberbullying prevention and response: Expert perspectives (pp. 13–36). Routledge.
Peng, Y., Zhu, Q., Wang, B., & Ren, J. (2020). A cross-sectional study on interference control: Age affects reactive control but not proactive control. PeerJ, 8, 1–14. https://doi.org/10.7717/peerj.8365
Pew Research Center. (2019). Social media fact sheet. https://www.pewresearch.org/internet/fact-sheet/social-media/
Quinn, D., Chen, L., & Mulvenna, M. (2013). Discovering social behaviour variances of younger and older users through social interaction analysis. International Journal of Web Science, 2(1–2), 44–65. https://doi.org/10.1504/IJWS.2013.056574
Quinn, D., Chen, L., Mulvenna, M. D., & Bond, R. (2016). Exploring the relationship between online social network site usage and the impact on quality of life for older and younger users: An interaction analysis. Journal of Medical Internet Research, 18(9), e245. https://doi.org/10.2196/jmir.5377
Ragelienė, T. (2016). Links of adolescents identity development and relationship with peers: A systematic literature review. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 25, 97–105.
Ševčíková, A., & Šmahel, D. (2009). Online harassment and cyberbullying in the Czech Republic: Comparison across age groups. Zeitschrift für Psychologie/Journal of Psychology, 217(4), 227. https://doi/10.1027/0044-3409.217.4.227
Sheridan, L. P., & Grant, T. (2007). Is cyberstalking different? Psychology, Crime & Law, 13(6), 627–640. https://doi.org/10.1080/10683160701340528
Stephenson--Abetz, J., & Holman, A. (2012). Home is where the heart is: Facebook and the negotiation of “old” and “new” during the transition to college. Western Journal of Communication, 76(2), 175–193. https://doi.org/10.1080/10570314.2011.654309
Subramanian, K. R. (2017). Influence of social media in interpersonal communication. International Journal of Scientific Progress and Research, 38(2), 70–75.
Sutcliffe, A. G., Binder, J. F., & Dunbar, R. I. (2018). Activity in social media and intimacy in social relationships. Computers in Human Behavior, 85, 227–235.
Wenner, J. R., & Randall, B. A. (2016). Predictors of prosocial behavior: Differences in middle aged and older adults. Personality and Individual Differences, 101, 322–326. https://doi.org/10.1016/j.paid.2016.05.367
Yang, C. (2018). Social media as more than a peer space: College freshmen encountering parents on Facebook. Journal of Adolescent Research, 33(4), 442–469. https://doi.org/10.1177/0743558416659750
Yang, C. C., Holden, S. M., & Carter, M. D. (2017). Emerging adults’ social media self-presentation and identity development at college transition: Mindfulness as a moderator. Journal of Applied Developmental Psychology, 52, 212–221. https://doi.org/10.1016/j.appdev.2017.08.006
Young, R., Len-Ríos, M., & Young, H. (2017). Romantic motivations for social media use, social comparison, and online aggression among adolescents. Computers in Human Behavior, 75, 385–395. https://doi-org.ezproxy.federation.edu.au/10.1016/j.chb.2017.04.021
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Branson, M., March, E., Marrington, J.Z. (2022). Talkin’ Bout My Generation: The Utility of Different Age Cohorts to Predict Antisocial Behaviour on Social Media. In: Machin, T., Brownlow, C., Abel, S., Gilmour, J. (eds) Social Media and Technology Across the Lifespan. Palgrave Studies in Cyberpsychology. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-99049-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-99049-7_3
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-030-99048-0
Online ISBN: 978-3-030-99049-7
eBook Packages: Behavioral Science and PsychologyBehavioral Science and Psychology (R0)