عنوان

Web content credibility /

(Number (ISBN

3319777947

(Number (ISBN

9783319777948

Erroneous ISBN

3319777939

Erroneous ISBN

9783319777931

Title Proper

Web content credibility /

General Material Designation

[Book]

First Statement of Responsibility

Adam Wierzbicki.

Place of Publication, Distribution, etc.

Cham, Switzerland :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

2018.

Specific Material Designation and Extent of Item

1 online resource (xii, 221 pages) :

Other Physical Details

illustrations

Text of Note

Includes bibliographical references and index.

Text of Note

Intro; Preface; Contents; 1 Introduction; 1.1 Credibility and Relevance of Web Content; 1.1.1 Credibility and Relevance in Human Communication; 1.1.2 Epistemic Similarities of Credibility and Relevance Judgments of Web Content; 1.2 Why Does Credibility Evaluation Support Matter on the Web?; 1.2.1 Examples of Non-credible Medical Web Content; 1.2.1.1 Vaccines and Autism; 1.2.1.2 Consuming Placenta; 1.2.1.3 Colloidal Silver; 1.2.2 Fake News in Web-Based Social Media; 1.2.3 Examples of Credibility Evaluation Support Systems; 1.2.3.1 Health on the Net; 1.2.3.2 WOT; 1.2.3.3 Snopes.

Text of Note

1.2.3.4 PolitiFact1.3 Book Organization; 2 Understanding and Measuring Credibility; 2.1 Credibility and Truth; 2.1.1 Post-structuralist Truth; 2.1.2 Scientific Truth; 2.1.3 Semantic Truth Theory; 2.1.4 Incompleteness and Undecidability of Truth; 2.2 What Does It Mean to Support Credibility Evaluation?; 2.3 Definitions of Credibility; 2.3.1 Source Credibility; 2.3.1.1 Credibility Trust and Reputation; 2.3.1.2 Reputation; 2.3.1.3 Normative Trust and Credibility Trust; 2.3.1.4 Source Credibility Defined as Trust; 2.3.2 Media and System Credibility; 2.3.3 Message Credibility.

Text of Note

2.3.4 Proposed Definition of Credibility2.3.5 Conclusion of Top-Down Discussion of Credibility; 2.4 Theories of Web Content Credibility; 2.4.1 Credibility Evaluation Checklists; 2.4.2 Iterative Model; 2.4.3 Predictive and Evaluative Model; 2.4.4 Fogg's Prominence-Interpretation Theory (2003); 2.4.5 Dual-Processing Model; 2.4.6 MAIN Model; 2.4.7 Ginsca's Model; 2.5 Measures of Credibility; 2.5.1 Ordinal and Cardinal Scales of Credibility; 2.5.2 Example Credibility Rating Scale; 2.5.3 Consensus Measures; 2.5.4 Distribution Similarity Tests; 2.5.5 The Earth Mover's Distance (EMD).

Text of Note

2.6 Credibility Measurement Experiments2.6.1 Fogg's Study; 2.6.2 Microsoft Credibility Corpus; 2.6.3 Panel Experiment (IIBR); 2.6.4 The Content Credibility Corpus; 2.6.4.1 C3 Dataset Augmentation with Tags; 2.6.5 Fake News Datasets; 2.7 Subjectivity of Credibility Measurements; 2.7.1 Robustness of Credibility Rating Distributions to Sample Composition; 2.8 Classes of Credibility; 2.8.1 Clustering Credibility Rating Distributions Using Earth Mover's Distance; 2.8.1.1 The AFT Dataset of Wikipedia Quality Ratings; 2.8.1.2 Clustering Algorithm; 2.8.1.3 Determining the Number of Clusters.

Text of Note

2.8.1.4 Notation for Extreme Distributions2.8.2 Classes of Credibility Based on Distributions; 2.8.2.1 Fitting of Proposed Classes to Distribution Clusters; 2.8.2.2 Fitting the Controversy Class to Discovered Clusters; 2.8.3 Advantage of Defining Classes Using Distributions Over Arithmetic Mean; 2.9 Credibility Evaluation Criteria; 2.9.1 Identifying Credibility Evaluation Criteria from Textual Justifications; 2.9.2 Independence of Credibility Evaluation Criteria; 2.9.3 Modeling Credibility Evaluations Using Credibility Criteria; 3 Supporting Online Credibility Evaluation.

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Text of Note

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. 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.

Source for Acquisition/Subscription Address

Springer

Title

Web content credibility.

International Standard Book Number

9783319777931

Web sites-- Evaluation.

Web sites-- Management.

COMPUTERS-- General.

Web sites-- Evaluation.

Web sites-- Management.

COM-- 000000

UDBD

UDBD

UNH

UNH

Number

Edition

Class number

Wierzbicki, Adam

Date of Transaction

20200823112548.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y