Mitigating Cyber Bullying

Reflective Portfolio
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Mitigating Cyber Bullying
Al-Garadi, M. A., Hussain, M. R., Khan, N., Murtaza, G., Nweke, H. F., Ali, I., ... & Gani, A. (2019). Predicting cyberbullying on social media in the big data era using machine learning algorithms: review of literature and open challenges. IEEE Access, 7, 70701-70718.’
Al-Garadi article assesses how various misuses of social media platforms have proven harmful to victims and how the development of prediction models can help curb this behavior. The article also discusses how cyberbullying detection works and the benefits it has for society. The article also exhibits that despite numerous challenges encountered when attempting to predict various cyberbullying behaviors using machine learning algorithms, the goal has significantly been met. As a result, the article will serve as a reliable source of information on the topic of cyberbullying.
Hellfeldt, K., López-Romero, L., & Andershed, H. (2020). Cyberbullying and psychological well-being in young adolescence: the potential protective mediation effects of social support from family, friends, and teachers. International journal of environmental research and public health, 17(1), 45.
The primary focus of Hellfeldt’s article is the relationship that exists between an individual who has experienced various forms of cyberbullying and their psychological well-being. Hellfeldt article also investigates how those who receive support from third parties are affected by cyberbullying in comparison to those who do not. The primary research method used was observation, with the behavior of various victims of cyberbullying being critically evaluated. The main findings were that individuals who were fortunate enough to receive social support from their teachers and parents following cyberbullying were less likely to become depressed. The article’s main limitation is that, despite the prevalence of cyberbullying, it is primarily focused on young adolescence alone. As a result, the article will be extremely useful in analyzing the impact of cyberbullying.
Ho, S. S., Lwin, M. O., Yee, A. Z., Sng, J. R., & Chen, L. (2019). Parents’ responses to cyber bullying effects: How third-person perception influences support for legislation and parental mediation strategies. Computers in Human Behavior, 92, 373-380.
Ho et al. emphasize in this article that third-party effects best explain how parents react to cyberbullying. The study’s main finding is that parents’ perceptions of cyberbullying are heavily influenced by their personal support for anti-cyberbullying legislation. The data used in this article came from a survey of 1187 parents, implying that the information provided is reliable. Another finding was that parents tend to believe that other people’s children are more likely to be victims of cyberbullying than their own. The article’s main limitation is that the information provided was primarily based on a survey of Singaporeans. As a result, the findings presented may not fully represent how parents worldwide deal with cyberbullying. The article provides useful background information on the topic of reducing the effects of cyberbullying.
Huang, J., Zhong, Z., Zhang, H., & Li, L. (2021). Cyber bullying in social media and online games among Chinese college students and its associated factors. International journal of environmental research and public health, 18(9), 4819.
Huang’s article investigates various acts of harassment that qualify as cyberbullying and how they can be detected on various social media platforms. The article’s main focus is on ensuring that, despite the development of various cyberbullying techniques, the time at which these acts are detected is effective. The harm caused by cyberbullying is reduced through timely detection. As a result, the article is viable in understanding cyberbullying because it proposes that cyberbullying cases can be controlled using data-driven approaches and the development of numerous automation.
López-Vizcaíno, M. F., Nóvoa, F. J., Carneiro, V., & Cacheda, F. (2021). Early detection of cyber bullying on social media networks. Future Generation Computer Systems, 118, 219-229.
López-Vizcaíno article focuses on the harm caused by cyberbullying and how it can be detected and avoided before it occurs. The article’s secondary goal is to evaluate the two approaches, threshold, and dual in the early detection of cyber bullying. The data used in this article came from a real-world dataset, and it showed that implementing any of the two approaches could improve the detection of cyberbullying by 42%. The article’s main limitation is that it only uses two models. Despite this, the article provided credible information that will be useful in analyzing cyberbullying.
Ortega-Barón, J., Buelga, S., Ayllón, E., Martínez-Ferrer, B., & Cava, M. J. (2019). Effects of intervention program Prev@ cib on traditional bullying and cyberbullying. International journal of environmental research and public health, 16(4), 527.
Ortega-Barón article exhibits that failure to address cyberbullying promptly may have various psychological consequences for the victims. The article examined cyberbullying programs that could be implemented to help ensure that cases of harassment on various online platforms are reduced. The main finding was that there was a recorded decrease in bullying and cyber victimization cases in the controlled groups after the two programs were introduced. The article’s main limitation was that it did not go into detail about how ...