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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract
This chapter introduces the problem of credibility evaluation on the Web. Practical examples of systems that support Web content credibility evaluation are discussed, along with examples of non-credible Web content, fake news, and their potential impact on Web users. The problem of credibility evaluation is compared to the problem of Web search and relevance judgment.
Adam Wierzbicki

Chapter 2. Understanding and Measuring Credibility

Abstract
This chapter creates a groundwork and conceptual foundation for the rest of the book. The chapter introduces a definition of information credibility and of Web content credibility evaluation support. Methods of measuring Web content credibility are discussed, along with available datasets, including fake news datasets. The subject of bias and subjectivity of Web content credibility evaluations is discussed.
Adam Wierzbicki

Chapter 3. Supporting Online Credibility Evaluation

Abstract
This chapter deals with methods and algorithms of Web content credibility evaluation support. The chapter introduces several examples of credibility evaluation support (CS) systems. A reference design of a CS system guides the reader. Various algorithms that are part of the CS system are discussed. Algorithms for automatic evaluation of statement credibility are discussed.
Adam Wierzbicki

Chapter 4. Credibility of Social Media

Abstract
This chapter deals with credibility evaluation on Web-based social media, in particular, Twitter, Q&A systems, and Wikipedia. The special characteristics of credibility evaluation support on each of these platforms are discussed in detail, along with the most successful approaches of credibility evaluation support. Algorithms for fake news detection are reviewed in this chapter.
Adam Wierzbicki

Chapter 5. Theoretical Models of Credibility

Abstract
This chapter introduces a theoretical model of Web content credibility that is based on the definition introduced in Chap. 2. The Credibility Game can be used to model reputed, surface, and earned credibility. The model is used to evaluate the effects of a reputation system (an important component of the CS system reference design introduced in Chap. 3) on the global behavior of content producers. The model can also be used to evaluate the effectiveness of methods for fake news detection.
Adam Wierzbicki

Chapter 6. Conclusions

Abstract
Evaluation of Web content credibility is becoming increasingly significant. Our personal, political, work-related, medical, and health decisions (as well as many others) are frequently made on the basis of information on the Web. A recent, and quite concerning, example of the impact of information on the Internet is the 2016 American presidential election [4]. This important political decision has been influenced by numerous allegations and rumors circulating on the Internet, concerning both main candidates.
Adam Wierzbicki

Backmatter

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