國立虎尾科技大學 |

Detecting fake news on social media /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Detecting fake news on social media // Kai Shu and Huan Liu.
作者:	Shu, Kai,
其他作者:	Liu, Huan,
面頁冊數:	1 PDF (xiii, 115 pages) :illustrations (chiefly color). :
附註:	Part of: Synthesis digital library of engineering and computer science.
標題:	Fake news. -
電子資源:	https://doi.org/10.2200/S00926ED1V01Y201906DMK018
電子資源:	https://ieeexplore.ieee.org/servlet/opac?bknumber=8758609
ISBN:	9781681735832

Detecting fake news on social media /
Shu, Kai,

Detecting fake news on social media /Kai Shu and Huan Liu. - 1 PDF (xiii, 115 pages) :illustrations (chiefly color). - Synthesis lectures on data mining and knowledge discovery,#182151-0075 ;. - Synthesis digital library of engineering and computer science..

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

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Compendex

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:

Mode of access: World Wide Web.

ISBN: 9781681735832

Standard No.: 10.2200/S00926ED1V01Y201906DMK018doiSubjects--Topical Terms:

1253120
Fake news.
Subjects--Index Terms:

fake newsIndex Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: PN4784.F27 / S584 2019eb

Dewey Class. No.: 070.43

Detecting fake news on social media /
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245 1 0 $a Detecting fake news on social media / $c Kai Shu and Huan Liu.
264 1 $a [San Rafael, California] : $b Morgan & Claypool, $c [2019]
300 $a 1 PDF (xiii, 115 pages) : $b illustrations (chiefly color).
336 $a text $2 rdacontent
337 $a electronic $2 isbdmedia
338 $a online resource $2 rdacarrier
490 1 $a Synthesis lectures on data mining and knowledge discovery, $x 2151-0075 ; $v #18
500 $a Part of: Synthesis digital library of engineering and computer science.
504 $a Includes bibliographical references (pages 97-113).
505 0 $a 1. Introduction -- 1.1. Motivation -- 1.2. An interdisciplinary view on fake news -- 1.3. Fake news in social media age
505 8 $a 2. What news content tells -- 2.1. Textual features -- 2.2. Visual features -- 2.3. Style features -- 2.4. Knowledge-based methods
505 8 $a 3. How social context helps -- 3.1. User-based detection -- 3.2. Post-based detection -- 3.3. Network-based detection
505 8 $a 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.
506 $a Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0 $a Compendex
510 0 $a INSPEC
510 0 $a Google scholar
510 0 $a Google book search
520 $a 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:
530 $a Also available in print.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Title from PDF title page (viewed on July 29, 2019).
650 0 $a Fake news. $3 1253120
650 0 $a Social media. $3 780265
650 0 $a Data mining. $3 528622
650 0 $a Machine learning. $3 561253
653 $a fake news
653 $a misinformation
653 $a disinformation
653 $a social computing
653 $a social media
653 $a data mining
653 $a social cyber security
653 $a machine learning
655 0 $a Electronic books. $2 local $3 554714
700 1 $a Liu, Huan, $e author. $3 1253119
776 0 8 $i Print version: $z 9781681735849 $z 9781681735825
830 0 $a Synthesis digital library of engineering and computer science. $3 598254
830 0 $a Synthesis lectures on data mining and knowledge discovery ; $v # 16. $x 2151-0075 $3 1253064
856 4 0 $3 Abstract with links to full text $u https://doi.org/10.2200/S00926ED1V01Y201906DMK018
856 4 2 $3 Abstract with links to resource $u https://ieeexplore.ieee.org/servlet/opac?bknumber=8758609