Online hate is a topic that has received considerable interest lately, as online hate represents a risk to self-determination and peaceful coexistence in societies around the globe. However, not much is known about the explanations for adolescents posting or forwarding hateful online material or how adolescents cope with this newly emerging online risk. Thus, we sought to better understand the relationship between a bystander to and perpetrator of online hate, and the moderating effects of problem-focused coping strategies (e.g., assertive, technical coping) within this relationship. Self-report questionnaires on witnessing and committing online hate and assertive and technical coping were completed by 6829 adolescents between 12 and 18 years of age from eight countries. The results showed that increases in witnessing online hate were positively related to being a perpetrator of online hate. Assertive and technical coping strategies were negatively related with perpetrating online hate. Bystanders of online hate reported fewer instances of perpetrating online hate when they reported higher levels of assertive and technical coping strategies, and more frequent instances of perpetrating online hate when they reported lower levels of assertive and technical coping strategies. In conclusion, our findings suggest that, if effective, prevention and intervention programs that target online hate should consider educating young people about problem-focused coping strategies, self-assertiveness, and media skills. Implications for future research are discussed.

Cyberhate represents a risk to adolescents’ development and peaceful coexistence in democratic societies. Yet, not much is known about the relationship between adolescents’ ability to cope with cyberhate and their cyberhate involvement. To fill current gaps in the literature and inform the development of media education programs, the present study investigated various coping strategies in a hypothetical cyberhate scenario as correlates for being cyberhate victims, perpetrators, and both victim–perpetrators. The sample consisted of 6829 adolescents aged 12–18 years old (M_age = 14.93, SD = 1.64; girls: 50.4%, boys: 48.9%, and 0.7% did not indicate their gender) from Asia, Europe, and North America. Results showed that adolescents who endorsed distal advice or endorsed technical coping showed a lower likelihood to be victims, perpetrators, or victim–perpetrators. In contrast, if adolescents felt helpless or endorsed retaliation to cope with cyberhate, they showed higher odds of being involved in cyberhate as victims, perpetrators, or victim–perpetrators. Finally, adolescents who endorsed close support as a coping strategy showed a lower likelihood to be victim–perpetrators, and adolescents who endorsed assertive coping showed higher odds of being victims. In conclusion, the results confirm the importance of addressing adolescents’ ability to deal with cyberhate to develop more tailored prevention approaches. More specifically, such initiatives should focus on adolescents who feel helpless or feel inclined to retaliate. In addition, adolescents should be educated to practice distal advice and technical coping when experiencing cyberhate. Implications for the design and instruction of evidence-based cyberhate prevention (e.g., online educational games, virtual learning environments) will be discussed.

INTRODUCTION: Presently, naturalistic observation is considered as critical in understanding, and predicting the complexities of feelings and sentiments. Emerging trends of social media has completely revolutionized the process of communication. Social media, microblogging, and other means of e-communication can be used for extracting the content to decode the quality, valence, and effectiveness of communication. OBJECTIVES: In this paper, we represent the explanatory urge of mental health assessment during a pandemic situation, especially in a smart city scenario. METHODS: We reviewed the role of sentimental analysis, as an emerging application tool for emotional and behavioural analysis for the population affected by a pandemic. This paper examines the prospect of analysing the sentiments through machine learning tools to understand, describe, and predict human behavior. CONCLUSION: Further analysis of this psychological e-content can be used to understand and predict the patterns of human sentiments.