Detecting fake news on social media /
By: Shu, Kai [author.].
Contributor(s): Liu, Huan [author.].
Material type:
BookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on data mining and knowledge discovery: #18.Publisher: [San Rafael, California] : Morgan & Claypool, [2019]Description: 1 PDF (xiii, 115 pages) : illustrations (chiefly color).Content type: text Media type: electronic Carrier type: online resourceISBN: 9781681735832.Subject(s): Fake news | Social media | Data mining | Machine learning | fake news | misinformation | disinformation | social computing | social media | data mining | social cyber security | machine learningGenre/Form: Electronic books.DDC classification: 070.43 Online resources: Abstract with links to full text | Abstract with links to resource Also available in print.| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
|
PK Kelkar Library, IIT Kanpur | Available | EBKE924 |
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Part of: Synthesis digital library of engineering and computer science.
Includes bibliographical references (pages 97-113).
1. Introduction -- 1.1. Motivation -- 1.2. An interdisciplinary view on fake news -- 1.3. Fake news in social media age
2. What news content tells -- 2.1. Textual features -- 2.2. Visual features -- 2.3. Style features -- 2.4. Knowledge-based methods
3. How social context helps -- 3.1. User-based detection -- 3.2. Post-based detection -- 3.3. Network-based detection
4. Challenging problems of fake news detection -- 4.1. Fake news early detection -- 4.2. Weakly supervised fake news detection -- 4.3. Explainable fake news detection.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
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In the past decade, social media has become increasingly popular for news consumption due to its easy access, fast dissemination, and low cost. However, social media also enables the wide propagation of "fake news," i.e., news with intentionally false information. Fake news on social media can have significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area that is attracting tremendous attention. This book, from a data mining perspective, introduces the basic concepts and characteristics of fake news across disciplines, reviews representative fake news detection methods in a principled way, and illustrates challenging issues of fake news detection on social media. In particular, we discussed the value of news content and social context, and important extensions to handle early detection, weakly-supervised detection, and explainable detection. The concepts, algorithms, and methods described in this lecture can help harness the power of social media to build effective and intelligent fake news detection systems. This book is an accessible introduction to the study of detecting fake news on social media. It is an essential reading for students, researchers, and practitioners to understand, manage, and excel in this area. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, datasets, tools used in this book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information:
Also available in print.
Title from PDF title page (viewed on July 29, 2019).
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