Bullying committed via modern technology is referred to as cyberbullying. It may happen on social media, chat services, gaming platforms, and mobile devices. It is a pattern of behavior meant to frighten, infuriate, or shame people who are the target. Gender specifically has a substantial influence on cyberbullying at the personal background level. The kind of social behavior and the number of online groups a person joins considerably impact the extent of cyberbullying at the level of Internet use and social network habits. Victims of cyberbullying may have a range of detrimental effects, including mental health issues, poor academic performance, a desire to drop out of school, and even suicidal thoughts. Bullies have a higher propensity to engage in violent behavior and abuse drugs.
Abaixo, Ghada M. “Cyberbullying on social media platforms among university students in the United Arab Emirates.” International Journal of Adolescence and Youth 25.1 (2020): 407-420. https://www.tandfonline.com/doi/abs/10.1080/02673843.2019.1669059
According to this article, it is not unexpected that young people are utilizing the internet and social media platforms to hurt each other, given how widely they are used. Cyberbullying has been shown to have harmful effects in previous studies; however, there have not been many studies in Arab communities looking at its manifestations and traits (Abaido 409). In light of these nations’ social and cultural norms, reporting instances of cyberbullying is another major issue. This article demonstrates unequivocally how drastically today’s children have changed due to technology’s rapid development and spread. Their lives rely heavily on technology; thus, limiting their access to these platforms will significantly impact them. These impacts must be considered when developing measures for the prevention and intervention of cyberbullying. This article affirms the significance of further studying the many forms of bullying that are understudied in many Arab nations owing to cultural and societal considerations (Abaido 416). This source will be of great help to help me in completing my final paper. This is because the source clearly states how cyberbullying has been done, especially by youths. This article also provides various solutions on how to curb cyberbullying.
Kwan, Irene, et al. “Cyberbullying and children and young people’s mental health: a systematic map of systematic reviews.” Cyberpsychology, Behavior, and Social Networking 23.2 (2020): 72–82. https://www.liebertpub.com/doi/abs/10.1089/cyber.2019.0370
Cyberbullying is a severe public health problem linked to significant unfavorable mental and psychosocial outcomes in children and young adults. A systematic mapping study was carried out to locate systematic studies that examined the connection between cyberbullying and young people’s mental and psychological consequences in order to assess the highest level of available evidence (Kwan et al. 76). This methodical map consolidates the material that is currently available at the review level and validates the gaps in the synthesis of longitudinal and qualitative research. According to the findings, cyberbullying will become more common and pernicious when hyperconnectivity brings people closer online (Kwan 81). This will need a comprehensive strategic strategy to protect vulnerable users and boost public trust in technology. This paper concludes that further research on the moderating variables affecting cyberbullying behaviors might enhance our understanding and guide the creation of specialized intervention programs to lessen the detrimental effects of this issue. I will benefit from this site as I finish my final paper. This is due to the source’s explicit description of cyberbullying, particularly by young people. This article offers other ways to stop cyberbullying as well.
Lozano-Blasco, Raquel, Alejandra Cortés-Pascual, and M. Pilar Latorre-Martínez. “Being a cyber victim and a cyberbully–The duality of cyberbullying: A meta-analysis.” Computers in human behavior 111 (2020): 106444.https://www.sciencedirect.com/science/article/pii/S0747563220301977
According to this article, cyberbullying has been recognized as a severe issue in every nation. The issue of duality in cyberbullying, in which a person simultaneously plays the roles of a cyber victim and a cyberbully, has not, however, received enough in-depth study. In a meta-regression analysis of the moderator factors of sex, age, and culture, only culture was significant and accounted for 66% of the variation (Lozano-Blasco et al. 111). The systematic research revealed that women with shaky familial ties comprised most of the cyberbullying victim category. According to longitudinal research, there is a correlation between reporting being a cyber victim in the initial survey waves and turning into a cyberbully in subsequent waves. Additionally, it was shown that the community of cyber victims-bullies was likelier to have various psychiatric diseases and interpersonal emotional problems. The authors of this article greatly researched cyberbullying. The articles give accurate findings by using various research. This article will help me answer my research question on cyberbullying in my final paper.
Muneer, Amgad, and Suliman Mohamed Fati. “A comparative analysis of machine learning techniques for cyberbullying detection on Twitter.” Future Internet 12.11 (2020): 187. https://www.mdpi.com/874404
According to this article, the rise of social media, especially Twitter, has created several problems since people do not comprehend the idea of free speech. One of these problems is cyberbullying, a serious global problem that impacts both the victims’ lives and society. Numerous initiatives to stop, avoid, or lessen cyberbullying have been proposed in the literature; however, because they depend on the victims’ interactions, they are impractical (Muneer et al. 187). Therefore, it is important to identify cyberbullying without the victims’ participation. Because it is accurate and instructive, I will incorporate this article in my final work. It suggested a cyber-bully detection model using several classifiers based on TF-IDF and Word2Vec feature extraction. I think the knowledge from this article will be useful for me in writing a fantastic paper.
Yao, Mengfan, Charalampos Chelmis, and Daphney-Stavroula Zois. “Cyberbullying ends here: Towards robust detection of cyberbullying in social media.” The World Wide Web Conference. 2019 (pp. 3427–3433). https://dl.acm.org/doi/abs/10.1145/3308558.3313462
In this article, numerous automated, data-driven systems have been developed with an emphasis on categorization accuracy in response to the potentially harmful impacts of cyberbullying. A series of negative messages a bully sends to a victim over time to hurt the victim is cyberbullying, a sort of abusive online conduct that is, despite its lack of clear definition, a repeating process (Yao et al. 3428). This article ignored the fact that this harassing behavior is recurrent in favor of focusing on harassment as a sign of cyberbullying. However, issuing a cyberbullying warning immediately after a hostile remark is discovered might result in many false positives. This article introduces Concise and Accurate Instagram Media Sessions Cyberbullying Detection. The writers of this essay conducted an extensive study on cyberbullying. Through the use of several studies, the publications provide reliable findings. This essay will be a huge asset in helping me respond to my research topic on cyberbullying in my final thesis.
Works Cited
Abaixo, Ghada M. “Cyberbullying on social media platforms among university students in the United Arab Emirates.” International Journal of Adolescence and Youth 25.1 (2020): 407-420. https://www.tandfonline.com/doi/abs/10.1080/02673843.2019.1669059
Kwan, Irene, et al. “Cyberbullying and children and young people’s mental health: a systematic map of systematic reviews.” Cyberpsychology, Behavior, and Social Networking 23.2 (2020): 72-82. https://www.liebertpub.com/doi/abs/10.1089/cyber.2019.0370
Lozano-Blasco, Raquel, Alejandra Cortés-Pascual, and M. Pilar Latorre-Martínez. “Being a cyber victim and a cyberbully–The duality of cyberbullying: A meta-analysis.” Computers in human behavior 111 (2020): 106444. https://www.sciencedirect.com/science/article/pii/S0747563220301977
Muneer, Amgad, and Suliman Mohamed Fati. “A comparative analysis of machine learning techniques for cyberbullying detection on Twitter.” Future Internet 12.11 (2020): 187. https://www.mdpi.com/874404
Yao, Mengfan, Charalampos Chelmis, and Daphney-Stavroula Zois. “Cyberbullying ends here: Towards robust detection of cyberbullying in social media.” The World Wide Web Conference. 2019 (pp. 3427–3433). https://dl.acm.org/doi/abs/10.1145/3308558.3313462
write