This paper attempts to mitigate this gap within the literature concerning the use of social media for cyber engagement (CE) among students. Since students often become upset when network providers intervene, this paper aims to develop a model to measure ethics issues related to engagement with social media. The conducted survey examines social media use with regard to cyber engagement, cyberbullying behaviors, and being bullied, harassed, and stalked. To achieve the objective, this paper employed a questionnaire as the main data collection method and distributed it to 242 students, all of whom use social media. The findings were obtained via a quantitative research method, structural equation modeling, and partial least squares. The findings from our empirical study indicate that the assessment of discriminant validity has become an extensively acknowledged requirement for the analysis of latent variables' relationships. Goodness of fit indices demonstrates a good fit of the model. Roughly more than half of students indicated they had been bullied, harassed, and stalked online. The proposed model will help campus administration and decision makers to formulate strategies that can significantly reduce cyber harassment among students.INDEX TERMS Social media used, cyber harassment, cyberstalking, cyber bullying.

No abstract

The proposed system framework consists two main databases: Lexicon dictionary and Summarized previous cases, by depending on Senti-ment analysis and N-Gram algorithms to match the terms and documents. In the first branch, the judge opens the cyber case and therefore the system will highlight the technical terms automatically. Furthermore, the technical terms matched with Lexicon dictionary will be high-lighted. After that, the judge opens the highlighted terms (as links), and description page will be appeared. The description page contains details about the technical terms (definitions, explanations, examples, etc). On the other side, the second branch aims to retrieve the related legal cases (from the database) judged by courts in UK and KSA. The related cases are the most closed cases to the current legal case by inserting keywords based on the current case. The judge benefits from these cases through the judgment issued to give the fair judgment. N-gram algorithm is used to find the related cases because it has smart approach to expect the most closed document and texts. The system provides the judge with laws used in issuing the judgment in KSA and UK courts.