Combatting Cyberbullying in Digital Media with Artificial Intelligence

Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide.

Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts.

Key Features:

• Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms.
• Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence.
• Includes many case studies and applications of machine intelligence for combating cyberbullying.

Mohamed Lahby is Associate Professor at the Higher Normal School (ENS) University Hassan II of Casablanca, Morocco. His PhD in Computer Science from University Hassan II of Casablanca, in 2013. His research interests are smart cities and machine learning. He has published more than 50 papers.

Al-Sakib Khan Pathan is currently a Professor at the CSE department, United International University (UIU), Bangladesh. He received Ph.D. in Computer Engineering (2009) from Kyung Hee University, South Korea and B.Sc. in Computer Science and Information Technology (2003) from Islamic University of Technology (IUT), Bangladesh. He has served as a Chair and Committee Member in numerous top-ranked conferences and in editorial roles of several renowned journals. He is a Senior Member of IEEE.

Yassine Maleh is a cybersecurity professor and practitioner with industry and academic experience. He received a Ph.D. degree in Computer Sciences. Since 2019, he has been working as a professor of cybersecurity at Sultan Moulay Slimane University, Morocco. He was a Former CISO at the National Port Agency, Morocco, between 2012 and 2019. His research interests include information security and privacy, Internet of Things, networks security, information system, and IT governance.