Detecting fake news on social media:
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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
San Rafael, California
Morgan & Claypool
[2019]
|
| Schriftenreihe: | Synthesis lectures on data mining and knowledge discovery
18 |
| Schlagworte: | |
| Online-Zugang: | BFP01 TUM01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | Part of: Synthesis digital library of engineering and computer science Title from PDF title page (viewed on July 29, 2019) |
| Beschreibung: | 1 Online-Resource (xiii, 115 pages) illustrations (chiefly color) |
| ISBN: | 9781681735832 |
| DOI: | 10.2200/S00926ED1V01Y201906DMK018 |
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| 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 | ||
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Datensatz im Suchindex
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| any_adam_object | |
| author | Shu, Kai |
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| dewey-ones | 070 - Documentary, educational, news media; journalism |
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| id | DE-604.BV046427709 |
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| indexdate | 2024-07-10T08:44:19Z |
| institution | BVB |
| isbn | 9781681735832 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031840011 |
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| spelling | Shu, Kai Verfasser (DE-588)1203212976 aut Detecting fake news on social media Kai Shu and Huan Liu San Rafael, California Morgan & Claypool [2019] 1 Online-Resource (xiii, 115 pages) illustrations (chiefly color) txt rdacontent c rdamedia cr rdacarrier Synthesis lectures on data mining and knowledge discovery 18 Part of: Synthesis digital library of engineering and computer science Title from PDF title page (viewed on July 29, 2019) 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 Fake news Social media Data mining Machine learning Identifikation (DE-588)4072712-9 gnd rswk-swf Computerunterstütztes Verfahren (DE-588)4139030-1 gnd rswk-swf Desinformation (DE-588)4252093-9 gnd rswk-swf Falschmeldung (DE-588)4294308-5 gnd rswk-swf Social Media (DE-588)4639271-3 gnd rswk-swf Social Media (DE-588)4639271-3 s Falschmeldung (DE-588)4294308-5 s Desinformation (DE-588)4252093-9 s Identifikation (DE-588)4072712-9 s Computerunterstütztes Verfahren (DE-588)4139030-1 s DE-604 Liu, Huan 1958- Sonstige (DE-588)138749736 oth Erscheint auch als Druck-Ausgabe 978-1-68173-584-9 978-1-68173-582-5 https://doi.org/10.2200/S00926ED1V01Y201906DMK018 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Shu, Kai Detecting fake news on social media Fake news Social media Data mining Machine learning Identifikation (DE-588)4072712-9 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd Desinformation (DE-588)4252093-9 gnd Falschmeldung (DE-588)4294308-5 gnd Social Media (DE-588)4639271-3 gnd |
| subject_GND | (DE-588)4072712-9 (DE-588)4139030-1 (DE-588)4252093-9 (DE-588)4294308-5 (DE-588)4639271-3 |
| title | Detecting fake news on social media |
| title_auth | Detecting fake news on social media |
| title_exact_search | Detecting fake news on social media |
| title_full | Detecting fake news on social media Kai Shu and Huan Liu |
| title_fullStr | Detecting fake news on social media Kai Shu and Huan Liu |
| title_full_unstemmed | Detecting fake news on social media Kai Shu and Huan Liu |
| title_short | Detecting fake news on social media |
| title_sort | detecting fake news on social media |
| topic | Fake news Social media Data mining Machine learning Identifikation (DE-588)4072712-9 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd Desinformation (DE-588)4252093-9 gnd Falschmeldung (DE-588)4294308-5 gnd Social Media (DE-588)4639271-3 gnd |
| topic_facet | Fake news Social media Data mining Machine learning Identifikation Computerunterstütztes Verfahren Desinformation Falschmeldung Social Media |
| url | https://doi.org/10.2200/S00926ED1V01Y201906DMK018 |
| work_keys_str_mv | AT shukai detectingfakenewsonsocialmedia AT liuhuan detectingfakenewsonsocialmedia |