Generative AI and Cyberbullying

Cover
Half Title
Title
Copyright
Dedication
Contents
Acknowledgments
Chapter 1 Introduction: My Experiences as A Bullying Victim
	1.1 What Is Cyberbullying?
	1.2 The Differences between Traditional Bullying and Cyberbullying
	1.3 The Stages of Cyberbullying
	1.4 The Differences between Cyberbullying, Cyberstalking, and Cyberharassment
	1.5 The Evolution of Cyberbullying
	1.6 The Different Types of Cyberbullying
	1.7 The Impacts of Cyberbullying by Category
		1.7.1 Cyberbullying and Kids
		1.7.2 The Statistics of Cyberbullying on Kids
		1.7.3 Cyberbullying and Adults
		1.7.4 Cyberbullying and the Workplace
		1.7.5 Cyberbullying and Social Media Platforms
	1.8 Prelude to Generative AI
	Chapter 1 Resources
Chapter 2 The Use of Technology to Combat Cyberbullying
	2.1 The Top Anti-Cyberbullying Apps
	2.2 The Use of Parental Monitoring Mobile Apps
	2.3 The Top Parental Monitoring Mobile Apps
	2.4 The Other Ways That Anti-Cyberbullying Apps Can Be Used
	2.5 The Startups Leading the Way in Innovations Using Generative AI
	2.6 The Creation of Anti-Cyberbullying Mobile Apps
		2.6.1 The Top Mistakes That Are Made by Software Developers
		2.6.2 How These Mistakes Can Be Rectified
	2.7 Gauging the Effectiveness of an Anti-Cyberbullying Mobile App
	2.8 The Definition of Technological Acceptance
		2.8.1 The Theoretical Components
		2.8.2 The Technology Acceptance Models
		2.8.3 The Survey Instrument
	2.9 The Perceived Usefulness
	2.10 The Perceived Ease of Use
	2.11 The Attitude
		2.11.1 The Survey Instrument for the Anti-Cyberbullying Mobile App
	2.12 The Perceived Usefulness
	2.13 The Perceived Ease of Use
	2.14 The Attitude
	2.15 The Scientific Limitations Presented by the Technology Acceptance Model
		2.15.1 What It Means to Generative AI
	Chapter 2 Resource
Chapter 3 The Basics of Generative AI
	3.1 How Generative AI Fits In
	3.2 The Outputs That Are Created from Generative AI
	3.3 The Use of Natural Language Processing
		3.3.1 The Concept of the N-Gram
		3.3.2 The N-Gram and Probabilistic Models
	3.4 The Neural Network
	Chapter 3 Resources
Chapter 4 Advanced Topics Into Generative AI
	4.1 The Variational Autoencoder
	4.2 The General Adversarial Network
	4.3 The Diffusion Model
	4.4 The Types and Kinds of Diffusion Models
	4.5 The DALL-E 2
		4.5.1 The Mechanics of the “CLIP”
	4.6 The Top Part
	4.7 The Bottom Part
	4.8 The Stable Diffusion
	Chapter 4 Resource
Chapter 5 Conclusions
	Chapter 5 Resources
Appendix A: Generative Deep Learning
Index