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.
