Social Computing With Artificial Intelligence

This book provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers’ understanding of the topics addressed, it includes extensive data and a large number of charts and references, covering theories, techniques and applications. It particularly focuses on data collection, data mining, artificial intelligence algorithms in social computing, and several key applications of social computing application, and also discusses network propagation mechanisms and dynamic analysis, which provide useful insights into how information is disseminated in online social networks. This book is intended for readers with a basic knowledge of advanced mathematics and computer science.

Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023), July 20–24, 2023, San Francisco, USA

Will your next doctor be a human being—or a machine? Will you have a choice? If you do, what should you know before making it?This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to "reach off the Web" into the real world. The convergence of AI, social networking, and modern computing is creating an historic inflection point in the partnership between human beings and machines with potentially profound impacts on the future not only of computing but of our world and species.AI experts and researchers James Hendler—co-originator of the Semantic Web (Web 3.0)—and Alice Mulvehill—developer of AI-based operational systems for DARPA, the Air Force, and NASA—explore the social implications of AI systems in the context of a close examination of the technologies that make them possible. The authors critically evaluate the utopian claims and dystopian counterclaims of AI prognosticators. Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity is your richly illustrated field guide to the future of your machine-mediated relationships with other human beings and with increasingly intelligent machines. What Readers Will Learn What the concept of a social machine is and how the activities of non-programmers are contributing to machine intelligence How modern artificial intelligence technologies, such as Watson, are evolving and how they process knowledge from both carefully produced information (such as Wikipedia and journal articles) and from big data collections The fundamentals of neuromorphic computing, knowledge graph search, and linked data, as well as the basic technology concepts that underlie networking applications such as Facebook and Twitter How the change in attitudes towards cooperative work on the Web, especially in the younger demographic, is critical to the future of Web applications Who This Book Is ForGeneral readers and technically engaged developers, entrepreneurs, and technologists interested in the threats and promises of the accelerating convergence of artificial intelligence with social networks and mobile web technologies.

Proceedings of the AHFE International Conference on Human Factors in Design, Engineering, and Computing (AHFE 2023 Hawaii Edition), Honolulu, Hawaii, USA 4-6, December 2023

Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. Provides insights into the latest research trends in social network analysis Covers a broad range of data mining tools and methods for social computing and analysis Includes practical examples and case studies across a range of tools and methods Features coding examples and supplementary data sets in every chapter

This book constitutes the refereed proceedings of the 8th International Conference on Social Computing and Social Media, SCSM 2016, held as part of the 18th International Conference on Human-Computer Interaction, HCII 2016, held in Toronto, ON, Canada, in July 2016. The total of 1287 papers and 186 posters presented at the HCII 2016 conferences were carefully reviewed and selected from 4354 submissions. The papers thoroughly cover the entire field of Human-Computer Interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The 43 contributions included in the SCSM 2016 proceedings were organized in the following topical sections: designing and developing social media; users behaviour in social media; social media, policy, politics and engagement; social network analysis; social media in learning and collaboration; and enterprise social media.

Responding to the increasingly blurred boundaries between humans and technology, this innovative Handbook reveals the intricate patterns of interaction between individuals, machines, and organizations. Using cutting-edge data and analysis, expert contributors provide new insight into the rapidly growing digitalization of society.

This book constitutes the refereed proceedings of the First International Workshop, SOCIALEDU 2015, held in Stanford, CA, USA, in August 2015. The workshop aimed to discuss computational models of social computing applied to Digital Education. The 9 revised full papers presented were carefully reviewed and selected from 12 submissions. The papers address issues such as novel data mining and machine learning for social intelligence in digital education.- Social modelling and simulation to investigate social behaviours, emotional intelligence, influence processes and other social aspects that may influence learning performance in an educational environment.- Smart environments and interactive systems of social computing in digital education.- Analysis of social media and media intelligence in digital education.- Mobile social gaming in digital education.- The utilization of mobile and wearable technology in social systems in digital education, and others.