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  • Open Access

    ARTICLE

    A Deep Learning Framework for Arabic Cyberbullying Detection in Social Networks

    Yahya Tashtoush1,*, Areen Banysalim1, Majdi Maabreh2, Shorouq Al-Eidi3, Ola Karajeh4, Plamen Zahariev5

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3113-3134, 2025, DOI:10.32604/cmc.2025.062724 - 16 April 2025

    Abstract Social media has emerged as one of the most transformative developments on the internet, revolutionizing the way people communicate and interact. However, alongside its benefits, social media has also given rise to significant challenges, one of the most pressing being cyberbullying. This issue has become a major concern in modern society, particularly due to its profound negative impacts on the mental health and well-being of its victims. In the Arab world, where social media usage is exceptionally high, cyberbullying has become increasingly prevalent, necessitating urgent attention. Early detection of harmful online behavior is critical to… More >

  • Open Access

    ARTICLE

    Leveraging Transformers for Detection of Arabic Cyberbullying on Social Media: Hybrid Arabic Transformers

    Amjad A. Alsuwaylimi1,*, Zaid S. Alenezi2

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3165-3185, 2025, DOI:10.32604/cmc.2025.061674 - 16 April 2025

    Abstract Cyberbullying is a remarkable issue in the Arabic-speaking world, affecting children, organizations, and businesses. Various efforts have been made to combat this problem through proposed models using machine learning (ML) and deep learning (DL) approaches utilizing natural language processing (NLP) methods and by proposing relevant datasets. However, most of these endeavors focused predominantly on the English language, leaving a substantial gap in addressing Arabic cyberbullying. Given the complexities of the Arabic language, transfer learning techniques and transformers present a promising approach to enhance the detection and classification of abusive content by leveraging large and pretrained… More >

  • Open Access

    ARTICLE

    Do Victims Defend Victims? The Mediating Role of Empathy between Victimization Experience and Public-Defending Tendency in School Bullying Situations

    Han Xie1, Yizhe Jiang1, Kunjie Cui2,*

    International Journal of Mental Health Promotion, Vol.26, No.12, pp. 1033-1043, 2024, DOI:10.32604/ijmhp.2024.056533 - 31 December 2024

    Abstract Objectives: This study investigates the association between victimization experience and the tendency to defend on behalf of victims during school bullying incidents in public settings, with a focus on the mediating effect of empathy and the moderating role of school level among Chinese children and adolescents. Methods: Data were collected by a cross-sectional survey. A total of 1491 students in Grades 4–11 participated (Boys = 52.8%; Meanage = 13.00 years, Standard Deviationage = 2.31). Structural equation modeling is employed to test the hypotheses. Results: The results indicate that empathy measures partially mediate the relationship between victimization experience… More >

  • Open Access

    ARTICLE

    Enhancing Arabic Cyberbullying Detection with End-to-End Transformer Model

    Mohamed A. Mahdi1, Suliman Mohamed Fati2,*, Mohamed A.G. Hazber1, Shahanawaj Ahamad3, Sawsan A. Saad4

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1651-1671, 2024, DOI:10.32604/cmes.2024.052291 - 27 September 2024

    Abstract Cyberbullying, a critical concern for digital safety, necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces. To tackle this challenge, our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers (BERT) base model (cased), originally pretrained in English. This model is uniquely adapted to recognize the intricate nuances of Arabic online communication, a key aspect often overlooked in conventional cyberbullying detection methods. Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media (SM) tweets showing a notable… More >

  • Open Access

    ARTICLE

    Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting

    Milos Dobrojevic1,4, Luka Jovanovic1, Lepa Babic3, Miroslav Cajic5, Tamara Zivkovic6, Miodrag Zivkovic2, Suresh Muthusamy7, Milos Antonijevic2, Nebojsa Bacanin2,4,8,9,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4997-5027, 2024, DOI:10.32604/cmc.2024.054459 - 12 September 2024

    Abstract Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones, computers, or tablets. It can occur through various channels, such as social media, text messages, online forums, or gaming platforms. Cyberbullying involves using technology to intentionally harm, harass, or intimidate others and may take different forms, including exclusion, doxing, impersonation, harassment, and cyberstalking. Unfortunately, due to the rapid growth of malicious internet users, this social phenomenon is becoming more frequent, and there is a huge need to address this issue. Therefore, the main goal of the research… More >

  • Open Access

    ARTICLE

    A Machine Learning Approach to Cyberbullying Detection in Arabic Tweets

    Dhiaa Musleh1, Atta Rahman1,*, Mohammed Abbas Alkherallah1, Menhal Kamel Al-Bohassan1, Mustafa Mohammed Alawami1, Hayder Ali Alsebaa1, Jawad Ali Alnemer1, Ghazi Fayez Al-Mutairi1, May Issa Aldossary2, Dalal A. Aldowaihi1, Fahd Alhaidari3

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1033-1054, 2024, DOI:10.32604/cmc.2024.048003 - 18 July 2024

    Abstract With the rapid growth of internet usage, a new situation has been created that enables practicing bullying. Cyberbullying has increased over the past decade, and it has the same adverse effects as face-to-face bullying, like anger, sadness, anxiety, and fear. With the anonymity people get on the internet, they tend to be more aggressive and express their emotions freely without considering the effects, which can be a reason for the increase in cyberbullying and it is the main motive behind the current study. This study presents a thorough background of cyberbullying and the techniques used… More >

  • Open Access

    ARTICLE

    The Relationship between Internet Addiction and Cyberbullying Perpetration: A Moderated Mediation Model of Moral Disengagement and Internet Literacy

    Wan Xiao1,*, Miaoting Cheng2,*

    International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1303-1311, 2023, DOI:10.32604/ijmhp.2023.042976 - 29 December 2023

    Abstract Internet addiction and cyberbullying have emerged as significant global mental health concerns in recent years. Although previous studies have shown a close association between Internet addiction and cyberbullying, the underlying mechanisms connecting these two phenomena remain unclear. Therefore, this study aimed to reveal the mechanisms involved between Internet addiction and cyberbullying perpetration from the perspective of cognition function. This study recruited 976 Chinese youth through online survey, using the short version of Internet Addiction Test (s-IAT), Chinese Cyberbullying Intervention Project Questionnaire (C-CIPQ), Cyberbullying Moral Disengagement Scale (CMDS), and Internet Literacy Questionnaire (ILQ) to investigate the More >

  • Open Access

    ARTICLE

    Cyberbullying Detection and Recognition with Type Determination Based on Machine Learning

    Khalid M. O. Nahar1,*, Mohammad Alauthman2, Saud Yonbawi3, Ammar Almomani4,5

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5307-5319, 2023, DOI:10.32604/cmc.2023.031848 - 29 April 2023

    Abstract Social media networks are becoming essential to our daily activities, and many issues are due to this great involvement in our lives. Cyberbullying is a social media network issue, a global crisis affecting the victims and society as a whole. It results from a misunderstanding regarding freedom of speech. In this work, we proposed a methodology for detecting such behaviors (bullying, harassment, and hate-related texts) using supervised machine learning algorithms (SVM, Naïve Bayes, Logistic regression, and random forest) and for predicting a topic associated with these text data using unsupervised natural language processing, such as More >

  • Open Access

    ARTICLE

    Methods Used to Reduce Bullying in Kindergarten from Teachers’ Perspectives

    Lina Bashatah*, Duaa Al-fifi

    International Journal of Mental Health Promotion, Vol.25, No.5, pp. 639-653, 2023, DOI:10.32604/ijmhp.2023.025878 - 28 April 2023

    Abstract This study identified the methods used by kindergarten teachers to reduce bullying among their students in and out of the classroom and examined differences based on the teachers’ years of experience and the number of courses on bullying they had taken. A descriptive survey using a questionnaire tool collected responses from 208 public kindergarten teachers in Riyadh, Kingdom of Saudi Arabia. The participants agreed with using such methods to reduce bullying among children as responding to parents’ reports and following up on the reasons for a child’s absence. They also agreed that bullying in the… More >

  • Open Access

    ARTICLE

    Firefly-CDDL: A Firefly-Based Algorithm for Cyberbullying Detection Based on Deep Learning

    Monirah Al-Ajlan*, Mourad Ykhlef

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 19-34, 2023, DOI:10.32604/cmc.2023.033753 - 06 February 2023

    Abstract There are several ethical issues that have arisen in recent years due to the ubiquity of the Internet and the popularity of social media and community platforms. Among them is cyberbullying, which is defined as any violent intentional action that is repeatedly conducted by individuals or groups using online channels against victims who are not able to react effectively. An alarmingly high percentage of people, especially teenagers, have reported being cyberbullied in recent years. A variety of approaches have been developed to detect cyberbullying, but they require time-consuming feature extraction and selection processes. Moreover, no… More >

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