Indian government initiatives on cyberbullying: A case study on cyberbullying in Indian higher education institutions

Kaur, Manpreet; Saini, Munish

doi:10.1007/s10639-022-11168-4

Cited by 29 publications

(11 citation statements)

References 42 publications

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“…Students in urban settings experienced cyberbullying and cyber-victimisation more frequently than those in rural settings. This was consistent with studies in India 64 and Taiwan. 65 This could be a result of greater access and exposure to the internet and communication technology in the urban areas compared with rural areas.…”

Section: Discussionsupporting

confidence: 93%

Cyberbullying and cyber-victimisation among higher secondary school adolescents in an urban city of Nepal: a cross-sectional study

Kunwar,

Sharma,

Marasini

et al. 2024

BMJ Open

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ObjectiveTo assess the prevalence and factors associated with cyberbullying and cyber-victimisation among high school adolescents of Pokhara Metropolitan City, Nepal.DesignA cross-sectional study.SettingPokhara Metropolitan City, Nepal.ParticipantsWe used convenient sampling to enrol 450 adolescents aged 16–19 years from four distinct higher secondary schools in Pokhara Metropolitan City.Outcome measuresWe administered the Cyberbullying and an Online Aggression Survey to determine the prevalence of cyberbullying and cyber-victimisation. Univariate and multivariate logistic regression analyses were performed to estimate the ORs and 95% CIs. Data were analysed using STATA V.13.ResultsThe 30-day prevalence of cyberbullying and cyber-victimisation was 14.4% and 19.8%, and the over-the-lifetime prevalence was 24.2% and 42.2%, respectively. Posting mean or hurtful comments online was the most common form of both cyberbullying and cyber-victimisation. Compared with females, males were more likely to be involved in cyberbullying (adjusted OR (AOR)=13.52; 95% CI: 6.04 to 30.25; p value <0.001) and cyber-victimised (AOR=2.22; 95% CI: 1.33 to 3.73; p value <0.05). Using the internet almost every day was associated with cyberbullying (AOR=9.44; 95% CI: 1.17 to 75.79; p value <0.05) and cyber-victimisation (AOR=4.96; 95% CI: 1.06 to 23.18; p value <0.05). Students from urban place of residence were associated with both cyberbullying (AOR=2.45; 95% CI: 1.23 to 4.88; p value <0.05) and cyber-victimisation (AOR=1.77; 95% CI: 1.02 to 3.05; p value <0.05).ConclusionThe study recommends the implementation of cyber-safety educational programmes, and counselling services including the rational use of internet and periodic screening for cyberbullying in educational institutions. The enforcement of strong anti-bullying policies and regulations could be helpful to combat the health-related consequences of cyberbullying.

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Section: Discussionsupporting

confidence: 93%

Cyberbullying and cyber-victimisation among higher secondary school adolescents in an urban city of Nepal: a cross-sectional study

Kunwar,

Sharma,

Marasini

et al. 2024

BMJ Open

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“…By directly addressing the psychological mechanisms underlying cyberbullying perpetration, we can potentially devise more effective prevention strategies. This would enable governments and administrators to implement a broader range of interventions to combat cyberbullying, such as nationwide projects initiated by governments [ 62 ]. Of course, further understanding the personality traits that trigger cyberbullying is also essential.…”

Section: Discussionmentioning

confidence: 99%

Moral disengagement, self-control and callous-unemotional traits as predictors of cyberbullying: a moderated mediation model

Li,

Guo,

2023

BMC Psychol

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Background Cyberbullying has become more prevalent, more difficult to detect, and more harmful to the victims. Whereas considerable prior work has investigated predictors and consequences of cyberbullying, additional research is needed to better understand the mechanisms by which these factors relate to cyberbullying perpetration and victimization. The goal of the present study was to examine the extent to which the link between individual differences in moral disengagement and cyberbullying perpetration is mediated by low self-control and, if so, whether this mediation effect varies by individuals’ degree of callous-unemotional traits. Method To explore these questions, we used cyberbullying, moral disengagement, self-control, and callous-unemotional traits scales and collected online survey data from a sample of 860 Chinese internet users aged 18 years old or older. Result As hypothesized, a significant positive relation between moral disengagement and cyberbullying emerged that was mediated by individual differences in self-control. Additionally, evidence of moderated mediation was found. That is, the indirect effect varied by degree of callous-unemotional traits, with a significantly stronger mediation effect (and association between self-control and cyberbullying) for individuals who were relatively higher in callous-unemotional traits. Conclusion We conclude that moral disengagement partially predicts cyberbullying through self-control, while callous-unemotional traits moderate the pathway between self-control and cyberbullying.

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“…In order to train a support vector machine for online harassment detection, the proposed system leverages ML-Approach to categorise the semantic meanings of uploaded messages. Manpreet Kaur and Munish Saini, "Indian government initiatives on cyberbullying: A case study on cyberbullying in Indian higher education institutions", 14 June 2022, Education and Information Technologies [4]. Cyberbullying involves the use of electronic means, including social media, to harass and harm the victim.…”

Section: Figure 2: Effects Of Intimidatormentioning

confidence: 99%

Shielding Online Communities: Natural Language Processing and Machine Learning Strategies against Social Media Intimidation

V K

2023

IJRAT

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With the usage of the internet and the growing prominence of communities, like social media we have witnessed a rise in cybercrime. Among these crimes one that stands out is Intimidator, which affects both people and adults alike. The increasing incidents of cyberbullying have led to consequences such as anxiety, aggression, depression and tragically even suicide. Consequently, there is now a pressing need for content regulation on social media platforms. This research focuses on developing a model of identifying text-based bullying messages and comments by categorizing them into five distinct types; Violence, Vulgar language Offensive content, sexually explicit material, and Hate Speech. The proposed approach involves utilizing Natural Language Processing (NLP) techniques with Machine Learning methods. The dataset is initially. Processed to remove information before extracting meaningful features. Finally, the model undergoes training and testing to ensure reliable results, in detecting instances of Intimidator in text-based data.

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Indian government initiatives on cyberbullying: A case study on cyberbullying in Indian higher education institutions

Cited by 29 publications

References 42 publications

Cyberbullying and cyber-victimisation among higher secondary school adolescents in an urban city of Nepal: a cross-sectional study

Cyberbullying and cyber-victimisation among higher secondary school adolescents in an urban city of Nepal: a cross-sectional study

Moral disengagement, self-control and callous-unemotional traits as predictors of cyberbullying: a moderated mediation model

Shielding Online Communities: Natural Language Processing and Machine Learning Strategies against Social Media Intimidation

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