Possible Solutions for Cyberbullying

  • Tatjana Petrović /
Keywords: cyberbullying, peer cyberbullying, artificial intelligence, machine learning, natural language processing

Abstract


The paper presents potential solutions for cyber violence, that is, the solutions for different forms of violence that are manifested in the cyber space. The paper begins with an overview of the theoretical framework, key features of cyberbullying and the roles that people can play in it. In this context, the paper points out the specifics of cyberbullying compared to the traditional bullying, while pointing out the relevant characteristics of the cyber space itself. Based on the consideration of the harmful consequences of cyberbullying, the paper points out the considerable danger of this phenomenon, and consequently, the necessity of its adequate suppression and prevention. In this regard, the paper will present possible solutions for cyber violence related to the application of modern technologies in cyber space. In particular, the paper discusses the importance of utilising information technologies in the fight against cyberbullying, through consideration of their application in the detection of cyberbullying based on the analysis of textual and other content. The capabilities of artificial intelligence and its related fields, that is, technologies that are applied in the suppression of cyber violence will be illustrated through specific projects and models developed for these purposes, which are also applied in cases of peer cyber violence. The paper also examines the possible ways of using certain technologies for providing support to victims of cyber violence.

References

Abaido, G. M. (2019). Cyberbullying on Social Media Platforms Among University Students in the United Arab Emirates. International Journal of Adolescence and Youth, 25(1), 407–420. Retrieved from: https://www.tandfonline.com/doi/full/10.1080/02673843.2019.1669059
Achuthan, K., Nair, V. K., Kowalski, R., Ramanathan, S., & Raman, R. (2023). Cyberbullying Research – Alignment to Sustainable Development and Impact of COVID-19: Bibliometrics and Science Mapping Analysis. Computers in Human Behavior, 140, 1-17.
Almomani, A., Nahar, K., Alauthman, M., Al-Betar, M. A., Yaseen, Q., & Gupta, B. B. (2024). Image Cyberbullying Detection and Recognition Using Transfer Deep Machine Learning. International Journal of Cognitive Computing in Engineering, 5, 14-26.
Baltezarević, V., Baltezarević, R. i Baltezarević, I. (2023). Sajber uznemiravanje dece sa posebnim osvrtom na digitalne igre. Temida, (26)2, 261-284.
Chua, Y. T., Parkin, S., Edwards, M., Oliveira, D., Schiffner, S., Tyson, G., & Hutchings, A. (2019). Identifying Unintended Harms of Cybersecurity Countermeasures. In: 2019 APWG Symposium on Electronic Crime Research (eCrime) (p. 1-15). New York: Institute of Electrical and Electronics Engineers.
Dinić, B. (2022). Digitalno nasilje. Novi Sad: Filozofski fakultet u Novom Sadu.
Gabrielli, S., Rizzi, S., Carbone, S., & Piras, E. M. (2021). School Interventions for Bullying-Cyberbullying Prevention in Adolescents: Insights from the UPRIGHT and CREEP Projects. International journal of environmental research and public health, 18(21), 1-13.
Huang, N., Zhang, S., Mu, Y., Yu, Y., Riem, M. M. E., & Guo, J. (2024). Does the COVID-19 Pandemic Increase or Decrease the Global Cyberbullying Behaviors? A Systematic Review and Meta-Analysis. Trauma, Violence & Abuse, 25(2), 1018–1035.
Ju, B. (2023). Impacts of Cyberbullying and Its Solutions. Advances in Humanities Research, 29, 254-258.
Kovačević, A. (2012). Primena web mininga i vizualizacije u otkrivanju sajber nasilja. U: Reagovanje na bezbednosne rizike u obrazovno-vaspitnim ustanovama (225-241). Beograd: Fakultet bezbednosti.
Kovačević, A., i Bajramović, J. (2018). Monitoring sajber nasilja. U: Bezbednost u obrazovno-vaspitnim ustanovama i video-nadzor (str. 111–126). Beograd: Fakultet bezbednosti.
Kuzmanović, D., Lajović, B., Grujić, S. i Medenica, G. (2016). Digitalno nasilje – prevencija i reagovanje. Beograd: Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije i Pedagoško društvo Srbije.
Mahmud, T., Ptaszynski, M., Eronen, J., & Masui, F. (2023). Cyberbullying Detection for Low-Resource Languages and Dialects: Review of the State of the Art. Information Processing & Management, 60(5), 1-52.
Milošević, M., i Putnik, N. (2019). Fenomen vršnjačkog nasilja na internetu – izazov za nauku i zakonodavstvo. Sociologija, 61(4), 599-616.
Milošević, T., Van Royen, K. & Davis, B. (2022). Artificial Intelligence to Address Cyberbullying, Harassment and Abuse: New Directions in the Midst of Complexity. International Journal of Bullying Prevention 4, 1–5.
Muneer, A., & Fati, S. M. (2020). A Comparative Analysis of Machine Learning Techniques for Cyberbullying Detection on Twitter. Future Internet, 12(11), 187.
Paul, S., Saha, S., & Singh, J. P. (2023). COVID-19 and Cyberbullying: Deep Ensemble Model to identify Cyberbullying from Code-Switched Languages during the Pandemic. Multimedia Tools and Applications, 82(6), 8773-8789.
Rakhmatov, D. (2022). Methods and Effectiveness of the Use of Artificial Intelligence in the Fight Against Cyberbullying. Journal of Academic Research and Trends in Educational Sciences, 1(4), 122-129.
Vismara, M., Girone, N., Conti, D., Nicolini, G., & Dell’Osso, B. (2022). The Current Status of Cyberbullying Research: A Short Review of the Literature. Current Opinion in Behavioral Sciences, 46, 1-17.
Zlatković, D. i Denić, N. (2019). Prevencija elektronskog nasilja. U: Zbornik radova sa 5. Međunarodnog savetovanja o upravljanju znanjem i informatici (str. 65-75). Novi Sad: Visoka tehnička škola strukovnih studija u Novom Sadu.
Published
2025/02/20
How to Cite
Petrović, T. (2024). Possible Solutions for Cyberbullying . International Journal of Contemporary Security Studies, 2(2). Retrieved from https://aseestant.ceon.rs/index.php/fb_godisnjak/article/view/51497
Section
Članci