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Social media content analysis[electronic resource] :natural language processing and beyond /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	302.231
書名/作者:	Social media content analysis : natural language processing and beyond // edited by Kam-Fai Wong...[et al.].
其他作者:	Wong, Kam-Fai.
出版者:	Singapore : : World Scientific,, c2018.
面頁冊數:	1 online resource (488 p.) : : ill. (some col.)
標題:	Online social networks - Social aspects.
標題:	Social media.
標題:	Natural language processing (Computer science)
標題:	Content analysis (Communication)
標題:	Electronic books.
ISBN:	9789813223615
書目註:	Includes bibliographical references.
摘要、提要註:	"Social media platforms have been ubiquitously used in our daily lives and are steadily transforming the ways people communicate, socialize and conduct business. However, the growing popularity of social media adversely leads to wild spread of unreliable information. This in turn inevitably creates serious pollution problem of the global social media environment, which is harmful against humanity. For example, President Donald Trump used social media strategically to win in the 2016 USA Presidential Election. But it was found that many messages he delivered over social media were unproven, if not untrue. This problem must be prevented at all cost and as soon as possible. Thus, analysis of social media content is a pressing issue. It is a timely and important research subject worldwide. However, the short and informal nature of social media messages renders conventional content analysis, which is based on natural language processing (NLP), ineffective. This volume consists of a collection of highly relevant scientific articles published by the authors in different international conferences and journals, and is divided into three distinct parts: (I) search and filtering; (II) opinion and sentiment analysis; and (III) event detection and summarization. This book presents the latest advances in NLP technologies for social media content analysis, especially content on microblogging platforms such as Twitter and Weibo."--Publisher's website.
電子資源:	http://www.worldscientific.com/worldscibooks/10.1142/10535#t=toc

Social media content analysis[electronic resource] :natural language processing and beyond /
Social media content analysisnatural language processing and beyond /[electronic resource] :edited by Kam-Fai Wong...[et al.]. - 1st ed. - Singapore :World Scientific,c2018. - 1 online resource (488 p.) :ill. (some col.) - Series on language processing, pattern recognition, and intelligent systems ;vol. 3. - Series on language processing, pattern recognition, and intelligent systems ;v. 2..

Includes bibliographical references.

"Social media platforms have been ubiquitously used in our daily lives and are steadily transforming the ways people communicate, socialize and conduct business. However, the growing popularity of social media adversely leads to wild spread of unreliable information. This in turn inevitably creates serious pollution problem of the global social media environment, which is harmful against humanity. For example, President Donald Trump used social media strategically to win in the 2016 USA Presidential Election. But it was found that many messages he delivered over social media were unproven, if not untrue. This problem must be prevented at all cost and as soon as possible. Thus, analysis of social media content is a pressing issue. It is a timely and important research subject worldwide. However, the short and informal nature of social media messages renders conventional content analysis, which is based on natural language processing (NLP), ineffective. This volume consists of a collection of highly relevant scientific articles published by the authors in different international conferences and journals, and is divided into three distinct parts: (I) search and filtering; (II) opinion and sentiment analysis; and (III) event detection and summarization. This book presents the latest advances in NLP technologies for social media content analysis, especially content on microblogging platforms such as Twitter and Weibo."--Publisher's website.

Mode of access: World Wide Web.

ISBN: 9789813223615Subjects--Topical Terms:

684230
Online social networks
--Social aspects.

LC Class. No.: HM742 / .S63 2018

Dewey Class. No.: 302.231

Social media content analysis[electronic resource] :natural language processing and beyond /
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490 1 $a Series on language processing, pattern recognition, and intelligent systems ; $v vol. 3
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520 $a "Social media platforms have been ubiquitously used in our daily lives and are steadily transforming the ways people communicate, socialize and conduct business. However, the growing popularity of social media adversely leads to wild spread of unreliable information. This in turn inevitably creates serious pollution problem of the global social media environment, which is harmful against humanity. For example, President Donald Trump used social media strategically to win in the 2016 USA Presidential Election. But it was found that many messages he delivered over social media were unproven, if not untrue. This problem must be prevented at all cost and as soon as possible. Thus, analysis of social media content is a pressing issue. It is a timely and important research subject worldwide. However, the short and informal nature of social media messages renders conventional content analysis, which is based on natural language processing (NLP), ineffective. This volume consists of a collection of highly relevant scientific articles published by the authors in different international conferences and journals, and is divided into three distinct parts: (I) search and filtering; (II) opinion and sentiment analysis; and (III) event detection and summarization. This book presents the latest advances in NLP technologies for social media content analysis, especially content on microblogging platforms such as Twitter and Weibo."--Publisher's website.
538 $a Mode of access: World Wide Web.
588 $a Description based on online resource; title from PDF title page (viewed October 12, 2017)
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856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/10535#t=toc