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010   $a3-319-77794-7
024 7 $a10.1007/978-3-319-77794-8
035   $a(CKB)3810000000358760
035   $a(MiAaPQ)EBC5446663
035   $a(DE-He213)978-3-319-77794-8
035   $a(PPN)229497470
035   $a(EXLCZ)993810000000358760
100   $a20180627d2018      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aWeb Content Credibility /$fby Adam Wierzbicki
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (225 pages)
311   $a3-319-77793-9 
327   $a1 Introduction -- 2 Understanding and Measuring Credibility -- 3 Supporting Online Credibility Evaluation -- 4 Credibility of Social Media -- 5 Theoretical Models of Credibility -- 6 Conclusions.
330   $aThis 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. Misinformation on the Internet, deliberate or merely out of ignorance, is a serious problem and it puts users in the position of needing strong critical thinking skills to sort wheat from chaff. This book will help. It's an impressive exploration of ideas in the area of Web content credibility evaluation support. ? Vint Cerf, Vice President and Chief Internet Evangelist at Google.
606   $aApplication software
606   $aUser interfaces (Computer systems)
606   $aMultimedia systems 
606   $aSoftware engineering
606   $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040
606   $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067
606   $aMedia Design$3https://scigraph.springernature.com/ontologies/product-market-codes/I25004
606   $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029
615  0$aApplication software.
615  0$aUser interfaces (Computer systems).
615  0$aMultimedia systems .
615  0$aSoftware engineering.
615 14$aInformation Systems Applications (incl. Internet).
615 24$aUser Interfaces and Human Computer Interaction.
615 24$aMedia Design.
615 24$aSoftware Engineering.
676   $a006.7
700   $aWierzbicki$b Adam$4aut$4http://id.loc.gov/vocabulary/relators/aut$0859928
906   $aBOOK
912   $a9910299284003321
996   $aWeb Content Credibility$91918850
997   $aUNINA