This book introduces readers to Web content credibility evaluation and evaluation support. It highlights empirical research and establishes a solid foundation for future research by presenting methods of supporting credibility evaluation of online content, together with publicly available datasets for reproducible experimentation, such as the Web Content Credibility Corpus. The book is divided into six chapters. After a general introduction in Chapter 1, including a brief survey of credibility evaluation in the social sciences, Chapter 2 presents definitions of credibility and related concepts of truth and trust. Next, Chapter 3 details methods, algorithms and user interfaces for systems supporting Web content credibility evaluation. In turn, Chapter 4 takes a closer look at the credibility of social media, exemplified in sections on Twitter, Q&A systems, and Wikipedia, as well as fake news detection. In closing, Chapter 5 presents mathematical and simulation models of credibility evaluation, before a final round-up of the book is provided in Chapter 6. Overall, the book reviews and synthesizes the current state of the art in Web content credibility evaluation support and fake news detection. It provides researchers in academia and industry with both an incentive and a basis for future research and development of Web content credibility evaluation support services.

This book is an attempt to bring closer the greater vision of the development of Social Informatics. Social Informatics can be de?ned as a discipline of informatics that studies how information systems can realize social goals, use social concepts, or become sources of information about social phenomena. All of these research directions are present in this book: fairness is a social goal; trust is a social concept; and much of this book bases on the study of traces of Internet auctions (used also to drive social simulations) that are a rich source of information about social phenomena. The book has been written for an audience of graduate students working in the area of informatics and the social sciences, in an attempt to bridge the gap between the two disciplines. Because of this, the book avoids the use of excessive mathematical formalism, especially in Chapter 2 that attempts to summarize the theoretical basis of the two disciplines of trust and fa- ness management. Readers are usually directed to quoted literature for the purpose of studying mathematical proofs of the cited theorems.

This book introduces readers to Web content credibility evaluation and evaluation support. It highlights empirical research and establishes a solid foundation for future research by presenting methods of supporting credibility evaluation of online content, together with publicly available datasets for reproducible experimentation, such as the Web Content Credibility Corpus. The book is divided into six chapters. After a general introduction in Chapter 1, including a brief survey of credibility evaluation in the social sciences, Chapter 2 presents definitions of credibility and related concepts of truth and trust. Next, Chapter 3 details methods, algorithms and user interfaces for systems supporting Web content credibility evaluation. In turn, Chapter 4 takes a closer look at the credibility of social media, exemplified in sections on Twitter, Q&A systems, and Wikipedia, as well as fake news detection. In closing, Chapter 5 presents mathematical and simulation models of credibility evaluation, before a final round-up of the book is provided in Chapter 6. Overall, the book reviews and synthesizes the current state of the art in Web content credibility evaluation support and fake news detection. It provides researchers in academia and industry with both an incentive and a basis for future research and development of Web content credibility evaluation support services.

This book is an attempt to bring closer the greater vision of the development of Social Informatics. Social Informatics can be de?ned as a discipline of informatics that studies how information systems can realize social goals, use social concepts, or become sources of information about social phenomena. All of these research directions are present in this book: fairness is a social goal; trust is a social concept; and much of this book bases on the study of traces of Internet auctions (used also to drive social simulations) that are a rich source of information about social phenomena. The book has been written for an audience of graduate students working in the area of informatics and the social sciences, in an attempt to bridge the gap between the two disciplines. Because of this, the book avoids the use of excessive mathematical formalism, especially in Chapter 2 that attempts to summarize the theoretical basis of the two disciplines of trust and fa- ness management. Readers are usually directed to quoted literature for the purpose of studying mathematical proofs of the cited theorems.

This book constitutes the refereed post-proceedings of two workshops held at the 5th International Conference on Social Informatics, SocInfo 2013, in Kyoto, Japan, in November 2013: the First Workshop on Quality, Motivation and Coordination of Open Collaboration, QMC 2013 and the First International Workshop on Histoinformatics, HISTOINFORMATICS 2013. The 11 revised papers presented at the workshops were carefully reviewed and selected from numerous submissions. They cover specific areas of social informatics. The QMC 2013 workshop attracted papers on new algorithms and methods to improve the quality or to increase the motivation of open collaboration, to reduce the cost of financial motivation or to decrease the time needed to finish collaborative tasks. The papers presented at HISTOINFORMATICS 2013 aim at improving the interaction between computer science and historical science towards fostering a new research direction of computational history.

This book constitutes the refereed proceedings of the 12th International Conference and School of Network Science, NetSci-X 2016, held in Wroclaw, Poland, in January 2016. The 12 full and 6 short papers were carefully reviewed and selected from 59 submissions. The papers deal with the study of network models in domains ranging from biology and physics to computer science, from financial markets to cultural integration, and from social media to infectious diseases.