Exploratory Study on Awareness of Social Networking-Based Cybercrime in the Omani Community
Abstract
The study aimed to verify the credibility of awareness of social media-based cybercrime in a sample of Omani society. This study used the exploratory analytical method. The sample consisted of 170 individuals from the Omani community, and the sample was selected through a snowball sampling method. The study tool, based on previous research and content analysis of cybercrime studies, identified 16 items indicating awareness of social media-based cybercrime. Exploratory and confirmatory factor analyses were used to assess the appropriateness of the scale for the sample, and the scale yielded two dimensions that accounted for 53.1% of the total variance of the phenomenon. The scale demonstrated adequate reliability based on Cronbach's alpha and omega coefficients. A subsample of Omani citizens was selected from the study sample to examine the impact of demographic variables on cybercrime awareness subscales. The results indicated that demographic variables did not affect social networking-based cybercrime awareness. It can be concluded that awareness of cybercrime is a form of cyber awareness.
Downloads
References
Anderson, R., Barton, C., Böhme, R., Clayton, R., Van Eeten, M. J., Levi, M., ... & Savage, S. (2013). Measuring the cost of cybercrime. The economics of information security and privacy, 265-300.
Arribas-Bel, D., Kourtit, K., Nijkamp, P., & Steenbruggen, J. (2015). Cyber cities: social media as a tool for understanding cities. Applied Spatial Analysis and Policy, 8, 231-247.
Beran, T., & Li, Q. (2005). Cyber-harassment: A study of a new method for an old behavior. Journal of educational computing research, 32(3), 265.
Berne, S., Frisén, A., Schultze-Krumbholz, A., Scheithauer, H., Naruskov, K., Luik, P., ... & Zukauskiene, R. (2013). Cyberbullying assessment instruments: A systematic review. Aggression and violent behavior, 18(2), 320-334.
Bhandari, A., & Bimo, S. (2020). TikTok and the “algorithmized self”: A new model of online interaction. AoIR Selected Papers of Internet Research.
Bossler, A. M., & Berenblum, T. (2019). Introduction: new directions in cybercrime research. Journal of Crime and Justice, 42(5), 495-499.
Broadhurst, R., & Chang, L. Y. (2012). Cybercrime in Asia: trends and challenges. Handbook of Asian criminology, 49-63.
Das, S., & Nayak, T. (2013). Impact of cybercrime: Issues and challenges. International journal of engineering sciences & Emerging technologies, 6(2), 142-153.
Fakhrou, A. A., Adawi, T. R., & Moussa, M. A. (2022). Cybercrime Risk Fear Among University Students’ Social Networking Sites: Validity and Reliability. International Journal of Cyber Criminology, 16(1), 40-53.
Gálik, S. (2019). On human identity in cyberspace of digital media. European Journal of Tranformation Studies, 7(2), 33-44.
Gambhir, B. S., Habibkar, J., Sohrot, A., & Dhumal, R. (2022). Cybercrime Detection Using Live Sentiment Analysis. In Pattern Recognition and Data Analysis with Applications (pp. 409-419). Singapore: Springer Nature Singapore.
Giumetti, G. W., & Kowalski, R. M. (2022). Cyberbullying via social media and well-being. Current Opinion in Psychology, 45, 101314.
Gordon, S., & Ford, R. (2006). On the definition and classification of cybercrime. Journal in computer virology, 2, 13-20.
Gunitsky, S. (2015). Corrupting the cyber-commons: social media as a tool of autocratic stability. Perspectives on Politics, 13(1), 42-54.
Hazelwood, S. D., & Koon-Magnin, S. (2013). Cyber stalking and cyber harassment legislation in the United States: A qualitative analysis. International Journal of Cyber Criminology, 7(2), 155.
Khandelwal, S., & Chaudhary, A. (2022). COVID-19 pandemic & cyber security issues: Sentiment analysis and topic modeling approach. Journal of Discrete Mathematical Sciences and Cryptography, 25(4), 987-997.
Kirwan, G. (2016). Forensic cyberpsychology. In An Introduction to Cyberpsychology (pp. 161-174). Routledge.
Kumari, S., Saquib, Z., & Pawar, S. (2018, August). Machine learning approach for text classification in cybercrime. In 2018 Fourth international conference on computing communication control and automation (ICCUBEA) (pp. 1-6). IEEE.
Kurniawan, B. (2018). Tik tok popularism and nationalism: rethinking national identities and boundaries on millennial popular cultures in indonesian context. Proceedings of AICS-Social Sciences, 8, 83-90.
Li, T. B. Q. (2005). Cyber-harassment: A study of a new method for an old behavior. Journal of educational computing research, 32(3), 265-277.
Liu, J., Hebenton, B., & Jou, S. (2012). Progress of Asian criminology: editors’ introduction. In Handbook of Asian criminology (pp. 1-7). New York, NY: Springer New York.
Lozano-Blasco, R., Cortés-Pascual, A., & Latorre-Martínez, M. P. (2020). Being a cybervictim and a cyberbully–The duality of cyberbullying: A meta-analysis. Computers in human behavior, 111, 106444.
Mandal, S., Saha, B., & Nag, R. (2020). Exploiting aspect-classified sentiments for cyber-crime analysis and hack prediction. In Trends in Computational Intelligence, Security and Internet of Things: Third International Conference, ICCISIoT 2020, Tripura, India, December 29-30, 2020, Proceedings 3 (pp. 200-212). Springer International Publishing.
Moussa, M. A. (2020a). Emotional blackmail: theories and patterns (in Arabic). Amman- Jordon: Dar Al-Swaqe Aleimieh.
Moussa, M. A. (2020b). Sentiments analysis in Cyber reality between real and possible (in Arabic). Amman- Jordon: Dar Al-Swaqe Aleimieh.
Ramírez Sánchez, J., Campo-Archbold, A., Zapata Rozo, A., Díaz-López, D., Pastor-Galindo, J., Gómez Mármol, F., & Aponte Díaz, J. (2021). Uncovering cybercrimes in social media through natural language processing. Complexity, 2021, 1-15.
Rosa, H., Pereira, N., Ribeiro, R., Ferreira, P. C., Carvalho, J. P., Oliveira, S., ... & Trancoso, I. (2019). Automatic cyberbullying detection: A systematic review. Computers in Human Behavior, 93, 333-345.
Selkie, E. M., Fales, J. L., & Moreno, M. A. (2016). Cyberbullying prevalence among US middle and high school–aged adolescents: A systematic review and quality assessment. Journal of Adolescent Health, 58(2), 125-133.
Shu, K., Sliva, A., Sampson, J., & Liu, H. (2018). Understanding cyber-attack behaviors with sentimental information on social media. In Social, Cultural, and Behavioral Modeling: 11th International Conference, SBP-BRiMS 2018, Washington, DC, USA, July 10-13, 2018, Proceedings 11 (pp. 377-388). Springer International Publishing.
Sliva, A., Shu, K., & Liu, H. (2019). Using social media to understand cyber-attack behavior. In Advances in Human Factors, Business Management and Society: Proceedings of the AHFE 2018 International Conference on Human Factors, Business Management and Society, July 21-25, 2018, Loews Sapphire Falls Resort at Universal Studios, Orlando, Florida, USA 9 (pp. 636-645). Springer International Publishing.
Suler, J. R. (2002). Identity management in cyberspace. Journal of applied psychoanalytic studies, 4, 455-459.
Velasco, C. (2022, May). Cybercrime and Artificial Intelligence. An overview of the work of international organizations on criminal justice and the international applicable instruments. In ERA Forum (Vol. 23, No. 1, pp. 109-126). Berlin/Heidelberg: Springer Berlin Heidelberg.
Whittaker, E., & Kowalski, R. M. (2015). Cyberbullying via social media. Journal of school violence, 14(1), 11-29.
Zuo, H., & Wang, T. (2019). Analysis of Tik Tok user behavior from the perspective of popular culture. Frontiers in Art Research, 1(3).
Copyright (c) 2024 Mohammed khamis Alharbi, Shereen abdelgawad ahmed, Mahmoud Ali Moussa
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License: CC BY-NC
Creative Commons Rights Expression Language (CC REL)