Youth Cybercrime, Peer Networks, and Digital Deviance in Urban Lagos: A Social Learning Perspective

Youth cybercrime has emerged as a significant social and security challenge in urban Nigeria, yet explanations that focus primarily on economic deprivation and technological access often overlook the social processes through which cybercriminal behaviour is learned, normalized, and sustained. This study examines the role of peer networks in shaping youth involvement in cybercrime in urban Lagos from the perspective of Social Learning Theory. The study adopted a qualitative case study design and drew on data from focus group discussions and key informant interviews involving youths and relevant community, educational, and law-enforcement stakeholders in selected urban areas of Lagos State. Thematic analysis was employed to identify recurring patterns in participants’ accounts of peer influence, digital socialization, behavioural modelling, reinforcement, and the normalization of cybercrime. Findings indicate that peer networks constitute important informal learning environments in which young people are introduced to cybercrime techniques, acquire knowledge about fraudulent practices, develop shared vocabularies and identities, and receive social and material reinforcement for deviant behaviour. Participants further identified social media platforms and popular culture as extending these learning processes beyond physical peer groups by exposing young people to conspicuous consumption, successful cybercriminal personas, and narratives that portray fraudulent wealth as legitimate achievement. The study also found that perceived social acceptance, peer recognition, and the demonstration of financial success can reinforce continued participation, while weak condemnation within families and communities reduces the perceived stigma associated with cybercrime. The study concludes that youth cybercrime in urban Lagos should be understood not only as an individual or technological problem but also as a socially learned form of digital deviance embedded in peer relations and wider cultural environments. It recommends preventive interventions centred on positive peer mentorship, digital ethics education, community-based social learning, responsible media representation, and youth-oriented economic opportunities.

youth cybercrime, peer networks, digital deviance, Social Learning Theory, social media, Lagos, Nigeria

1. Adam, U. A., Mohammed, M. A., & Mohammed, H. I. (2025). Safeguarding Nigerian youths from cybercrime: Exploring the challenges and potential solutions. Kashere Journal of Politics and International Relations, 3(2), 15–24. [Google Scholar] [Crossref]

2. Adetunji, O., & Eze, M. (2022). Cybercrime and youth exclusion in post-colonial Nigeria. Journal of African Digital Cultures, 5(2), 88–104. https://doi.org/10.1080/23311886.2022.2045561 [Google Scholar] [Crossref]

3. Agnew, R. (1992). Foundation for a general strain theory of crime and delinquency. Criminology, 30(1), 47–88. https://doi.org/10.1111/j.1745-9125.1992.tb01093.x [Google Scholar] [Crossref]

4. Barlett, C. P., & Anderson, C. A. (2021). Materialism and online deviance: The dangers of consumerist orientation among youth. Computers in Human Behavior, 120, 106680. https://doi.org/10.1016/j.chb.2021.106680 [Google Scholar] [Crossref]

5. Button, M., & Cross, C. (2021). Cybercrime Today: The Changing Digital Landscape. Oxford University Press. https://doi.org/10.1093/bjc/azab024 [Google Scholar] [Crossref]

6. Chikwe, S., & Adebayo, T. (2024). Peer networks and cybercrime knowledge transmission in Nigeria. Journal of African Criminology, 10(1), 12–34. [Google Scholar] [Crossref]

7. Décary-Hétu, D., & Dupont, B. (2019). Cybercrime is (often) social: The role of social networks and communities in online crime. American Behavioral Scientist, 63(1), 5–21. https://doi.org/10.1177/0002764219827144 [Google Scholar] [Crossref]

8. Ebelogu, C. U., Ojo, S. D., Andeh, C. P., & Agu, E. O. (2019). Cybercrime, its adherent negative effects on Nigerian youths and the society at large: Possible solutions. International Journal of Advances in Scientific Research and Engineering, 5(12), 155–164. https://doi.org/10.31695/IJASRE.2019.33658 [Google Scholar] [Crossref]

9. Edeh, C. O., & Aluko, A. M. (2020). Unemployment and youth involvement in cybercrime in Nigeria: A structural perspective. International Journal of Cyber Criminology, 14(2), 327–340. https://doi.org/10.3390/criminology14020082 [Google Scholar] [Crossref]

10. Economic and Financial Crimes Commission (EFCC). (2023). Cybercrime report: Nigeria 2023. EFCC Publications. [Google Scholar] [Crossref]

11. Flynn, L. R., Goldsmith, R. E., & Pollitte, W. (2016). Materialism, status consumption, and market involved consumers. Psychology & Marketing, 33(9), 761-776. [Google Scholar] [Crossref]

12. Hargittai, E., & Marwick, A. (2022). The algorithmic tie between visibility and stress: Social media’s role in digital comparison. New Media & Society, 24(3), 456–473. https://doi.org/10.1177/14614448211065460 [Google Scholar] [Crossref]

13. Holt, T. J., & Bossler, A. M. (2020). Cybercrime in Progress: Theory and Prevention of Technology-Enabled Offenses (2nd ed.). Routledge. [Google Scholar] [Crossref]

14. Holt, T. J., Bossler, A. M., & Seigfried-Spellar, K. C. (2017). Cybercrime and digital forensics: An introduction. Routledge. https://doi.org/10.4324/9781315296944 [Google Scholar] [Crossref]

15. Ibrahim, H., & Chukwuma, J. (2021). Social media and youth morality: The case of Lagos cyber fraud. Journal of Sociology and Technology, 10(4), 33–47. https://doi.org/10.1080/20420922.2021.0123456 [Google Scholar] [Crossref]

16. Leukfeldt, E. R., & Holt, T. J. (2020). Examining the social organization of cybercrime. Deviant Behavior,41(8), 943–956. https://doi.org/10.1080/01639625.2019.1565514 [Google Scholar] [Crossref]

17. Leukfeldt, E., & Yar, M. (2020). The Routledge International Handbook of Internet Crime. Routledge. [Google Scholar] [Crossref]

18. Marwick, A. (2018). Status Update: Celebrity, Publicity, and Branding in the Social Media Age. Yale University Press. https://doi.org/10.1177/1461444817717094 [Google Scholar] [Crossref]

19. Merton, R. K. (1938). Social structure and anomie. American Sociological Review, 3(5), 672–682. https://doi.org/10.2307/2084686 [Google Scholar] [Crossref]

20. Moon, B., Britto, S., & Fritsch, B. (2020). Cyber strain and youth online deviance. Journal of Criminal Justice, 68, 101736. https://doi.org/10.1016/j.jcrimjus.2020.101736 [Google Scholar] [Crossref]

21. National Bureau of Statistics. (2023). Labour force statistics: Q1 2023. NBS. [Google Scholar] [Crossref]

22. Nigerian Communications Commission (NCC). (2023). Internet penetration statistics by state. https://www.ncc.gov.ng [Google Scholar] [Crossref]

23. Nguyen, T., Pham, L., & Hoang, K. (2021). Cybercrime rationalization and youth behavior in Southeast Asia. Asian Criminology, 16(2), 89–105. https://doi.org/10.1007/s11417-021-09344-1 [Google Scholar] [Crossref]

24. Ngo, F. T., & Paternoster, R. (2021). Financial strain and computer crime: A test of General Strain Theory. Criminology, 59(2), 315–343. https://doi.org/10.1177/00224278211008931 [Google Scholar] [Crossref]

25. Nwosu, U. W., & Alinnor, E. M. (2024). Cybercrime and youth unemployment in Nigeria: The drift towards an international economic law. Nigerian Journal of Legal Studies. [Google Scholar] [Crossref]

26. Obasi, O., & Balogun, O. (2021). Materialism and media narratives of fraud in Nigeria. Journal of African Media Studies, 13(4), 275–289. https://doi.org/10.1080/19392397.2021.1887430 [Google Scholar] [Crossref]

27. Ojiezele, M., & Adenuga, G. (2025). Technology and the Nigerian youth: An examination of the impact of the digital double-edged sword. Pakistan Journal of Integrated Social Sciences, 2(2). https://doi.org/10.51846/pjiss.v2i2.4600 [Google Scholar] [Crossref]

28. Onah, C., & Ogwuche, C. H. (2024). Cybercrimes and social media addictions: The role of perceived use of conversational AI among residents in Nigeria. Academic Journal of Psychology and Counseling, 5(2), 170–201. https://doi.org/10.22515/ajpc.v5i2.9067 [Google Scholar] [Crossref]

29. Runciman, W. G. (1966). Relative Deprivation and Social Justice: A Study of Attitudes to Social Inequality in Twentieth-Century England. University of California Press. [Google Scholar] [Crossref]

30. Smith, H. J., Pettigrew, T. F., & Pippin, G. M. (2012). Relative deprivation: A theoretical and meta-analytic review. Personality and Social Psychology Review, 16(3), 203–232. https://doi.org/10.1177/1088868311430825 [Google Scholar] [Crossref]

31. Uchime, V. O., Molokwu, U. C., & Ewa, O. O. (2024). War against cybercrime: Assessing the role of Nigerian governments in the promotion of cybercrime among Nigerian youths, 2000–2020. EBSU Journal of Social Sciences and Humanities, 14(4). [Google Scholar] [Crossref]

32. Van Deursen, A. J. A. M., van Dijk, J. A. G. M., & ten Klooster, P. (2020). The relationship between social media use and relative deprivation experiences. Computers in Human Behavior, 102, 107176. https://doi.org/10.1016/j.chb.2019.106320 [Google Scholar] [Crossref]

33. Wall, D., & Williams, M. (2020). Youth, cybercrime, and social comparison: A UK perspective. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 14(3), Article 4. https://doi.org/10.5817/CP2020-3-4 [Google Scholar] [Crossref]

34. Wilkinson, R., & Pickett, K. (2018). The Inner Level: How More Equal Societies Reduce Stress, Restore Sanity and Improve Everyone’s Well-Being. Penguin Books. [Google Scholar] [Crossref]

• The Impact of Digital Supply Chain Integration on Customer Experience in the E-Commerce Sector
• Analysis of the Implementation of Digital-Based Public Information Transparency and Public Communication at the District Attorney’s Office of Tasikmalaya City
• Development of Soft Skills in Schoolchildren: Integrating Pedagogical Strategies, Digital Technologies, and Community Practices
• Reconstructing the Civil Liability of Banks for Social Engineering Fraud in Indonesia’s Digital Banking Ecosystem: Vitiated Consent, Duty of Care and Risk-Based Loss Allocation