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.
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Table of Contents
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
Authors
Muskan Garg Mayo Clinic, Rochester, MN, USA.. 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. Deepika Koundal University of Petroleum and Energy Studies, Dehradun, IndiaIEEE Senior Member, WIE. Dr. Deepika Koundal is currently associated with the University of Petroleum and Energy Studies, Dehradun. She has 12 years of teaching and research experience at many reputed Universities of India. She received her Bachelor Degree in Computer Science and Engineering from Kurukshetra University, Kurukshetra, India and subsequently her Masters and Doctorate Degrees in Computer Science & Engineering from Panjab University, Chandigarh, India. Her Ph.D. thesis is focused on Automated delineation of thyroid nodules in Ultrasound Images. She is actively pursuing research in Medical Image Processing. She is the awardee of Research excellence award given by Chitkara University in 2019. She also received the recognition and honorary membership from Neutrosophic Science Association from University of Mexico for her outstanding publication. She has published more than 30 research articles in reputed SCI and Scopus indexed journals and conferences.
