Combatting Cyberbullying in Digital Media with Artificial Intelligence
Chapman & Hall/CRC (Verlag)
978-1-032-49188-2 (ISBN)
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.
Preface................................................................................................................
Part 1: Background
1. Deep Learning as a digital tool for the detection and prevention of cyberbullying
Renzo Seminario-Córdova, Miguel Ángel Cortez Oyola and Brian Chero Arana
2. Detection and Prevention of Cyberbullying in Social Media Using Cognitive Computational Analysis
Neha M V et al
3. Combating Cyberbullying in Social Networks: An Artificial Intelligence Approach
Sheetal Sharma and Ridhika Chatterjee
4. Explainable Artificial Intelligence for Cyberbullying Detection and Prevention in Social Media: A Conceptual Review
Nipuna Sankalpa Thalpage
Part 2: Machine Learning Techniques and Cyberbullying Detection
5. Combating Cyberbullying in Various Digital Media using Machine Learning
Biodoumoye George Bokoloa, Qingzhong Liua and Qingzhong Liua
6. Cyber-bullying Detection for Multimodal Data convolutional neural network with Butterfly Optimization
Kalimuthu Sivanantham et al
7. Automated detection and analysis of cyberbullying behavior using Machine learning
Rejuwan Shamim and Mohamed Lahby
Part 3: Natural Language Processing (NLP) and Cyberbullying Detection
8. A Sentiment-Aware Statistical Evaluation of Vawulence Tweets for Cyberbullying Analytics
Segun Michael Akintunde et al
9. Identifying Behaviours and Characteristics of Social Media Sexual Harassment on LinkedIn for AI NLP Purposes
Karim Darban and Smail Kabbaj
10. Arabic offensive language and hate speech detection using ensemble transformers and data augmentation
Ibtissam Touahri
Part 4: Case Studies and Future Trends
11. Cyberbullying Prevention Practices on Social Media and Future Challenges
M. Zaenul Muttaqin et al
12. Methods of Complex Network Analysis to screen for Cyberbullying
Santhosh Kumar Rajamani and Radha Srinivasan Iyer
13. Cyberbullying and Social Media: Implications for African Digital Space
Basil Osayin Daudu, Goddy Uwa Osimen and Kennedy Shuaibu
14. A study on the impact of Social Media & Cyber Bullying on teen girls in India
Swapna M P and Dr. G Satyavathy
| Erscheinungsdatum | 15.12.2023 |
|---|---|
| Zusatzinfo | 3 Tables, color; 41 Tables, black and white; 73 Line drawings, color; 27 Line drawings, black and white; 6 Halftones, color; 79 Illustrations, color; 27 Illustrations, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 580 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Recht / Steuern ► Privatrecht / Bürgerliches Recht ► IT-Recht | |
| ISBN-10 | 1-032-49188-4 / 1032491884 |
| ISBN-13 | 978-1-032-49188-2 / 9781032491882 |
| Zustand | Neuware |
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