Emotional AI and Human-AI Interactions in Social Networking makes readers aware of recent progress in this integrated discipline. Filling the existing vacuum in research in artificial intelligence with the application of social science, this book provides in-depth knowledge of human-AI interactions with social networking and increased use of the internet. Chapters integrating Emotional Artificial Intelligence, examining behavioral interventions, compassion, education, and healthcare, as well as social cognitive networking, including social brain networks, play a pivotal role in enhancing interdisciplinary studies in the field of social neuroscience and Emotional AI.
This volume is a must for those wanting to dive into this exciting field of social neuroscience AI.
- Serves as a guide on social cognitive neuroscience for mental health and emotional AI for behavioral interventions
- Details various technologies of human-AI interactions with social networking
- Includes sections on emotional AI in behavioral interventions, compassion, education and healthcare
Section 1: Overview
1. Introduction to Social Neuroscience
2. Social neuroscience and Emotional AI
3. Social Neuroscience and Human-Computer Interaction
Section 2: Emotional Artificial Intelligence
4. Emotional AI for Behavioral interventions
5. Emotional AI for Compassion
6. Emotional AI for Education
7. Emotional AI for Healthcare
Section 3: Social cognitive networking
8. Social Mental Health Care
9. Social Cognitive Networks
10. Social Influence and Dissemination Models
11. Network Analysis for Social Systems
Section 4: Human-AI and Social Networks
12. Human-AI: Cognitive Social Networks
13. Human-AI: Explainability and Responsibility
14. Human-AI: Social Brain Networks 15.Human-AI: Ethical Studies
Section 5: Open challenges
16. Open Research Directions in Social Neuroscience
Dr. Muskan Garg is working as a postdoctoral research fellow at Mayo Clinic, Rochester, Minnesota. She was previously working as Postdoctoral research associate at University of Florida and as an assistant professor in Thapar institute of engineering and technology, Patiala. Her research focuses on the problems in natural language processing, information retrieval, and social media analysis. She received her Masters and PhD from Panjab University, India. Prior to TIET, she worked as an assistant professor in Amity school of engineering and technology at Amity University. Her focus is on research and development of cutting-edge NLP approaches to solving problems of national and international importance and on initiation and broadening a new program in natural language processing (including a new NLP course series). Her current research interests are causal inference, mental health on social media, event detection and sentiment analysis. She contributes as a reviewer in The ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) and Expert Systems with Applications, and prestigious conferences such as ACL, ICWSM, and EACL. Dr. Deepika Koundal currently serves as a Senior Researcher at the University of Eastern Finland, specializing in artificial intelligence, computer vision, medical image processing, neuroimaging, and deep learning. She holds a B.Tech, M.Tech, and Ph.D. in Computer Science and Engineering and has received several prestigious accolades, including the MSCA Seal of Excellence from the European Commission. In 2023 and 2024, she was recognized as a top 2% researcher by Stanford University. Additionally, she is an Adjunct Researcher at Ho Chi Minh City Open University in Vietnam and a Senior Associate Professor at UPES, Dehradun, India. Dr. Koundal has earned multiple research excellence awards from UPES and has published numerous research articles, edited notable books, and holds several patents. Furthermore, she contributes as a guest and associate editor for leading journals, including those published by IEEE and Elsevier.
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