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Social network analytics for contemporary business organizations[electronic resource] /

Record Type:	Electronic resources : Monograph/item
[NT 15000414]:	302.30285
Title/Author:	Social network analytics for contemporary business organizations/ Himani Bansal, Guishan Shrivastava, Gia Nhu Nguyen and Loredana-Mihaela Stanciu, editors.
other author:	Bansal, Himani,
Published:	Hershey, Pennsylvania : : IGI Global,, [2018]
Description:	1 online resource (xviii, 321 p.)
Subject:	Online social networks.
Subject:	Social sciences - Network analysis.
Subject:	Data mining.
Subject:	Computational linguistics.
ISBN:	9781522550983 (ebook)
ISBN:	9781522550976 (hardcover)
[NT 15000227]:	Includes bibliographical references and index.
[NT 15000228]:	Chapter 1. Social network analysis: tools, techniques, and technologies -- Chapter 2. Social networking data analysis tools and services -- Chapter 3. Social implications of e-government -- Chapter 4. Thwarting spam on Facebook: identifying spam posts using machine learning techniques -- Chapter 5. Impact of sarcasm in sentiment analysis methodology -- Chapter 6. Analysis of online social networks for the identification of sarcasm -- Chapter 7. A novel algorithm for sentiment analysis of online movie reviews -- Chapter 8. Authorship attribution for online social media -- Chapter 9. Business-oriented analytics with social network of things -- Chapter 10. Social aware cognitive radio networks: effectiveness of social networks as a strategic tool for organizational business management -- Chapter 11. An experimental evaluation of link prediction for movie suggestions using social media content -- Chapter 12. Knowledge discovery using data stream mining: an analytical approach -- Chapter 13. Trust and credibility analysis of websites: role of trust and credibility in evaluating online content.
[NT 15000229]:	"This book addresses different aspects such as sentiment analyzing with sarcasm detection, issues in data consolidation, and various challenges with dependability and trust analytics, automation of content extraction and an assortment of applications of business applications in social media analytics using machine learning, evolutionary algorithms and other techniques"--
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5097-6

Social network analytics for contemporary business organizations[electronic resource] /
Social network analytics for contemporary business organizations[electronic resource] /Himani Bansal, Guishan Shrivastava, Gia Nhu Nguyen and Loredana-Mihaela Stanciu, editors. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xviii, 321 p.)

Includes bibliographical references and index.

Chapter 1. Social network analysis: tools, techniques, and technologies -- Chapter 2. Social networking data analysis tools and services -- Chapter 3. Social implications of e-government -- Chapter 4. Thwarting spam on Facebook: identifying spam posts using machine learning techniques -- Chapter 5. Impact of sarcasm in sentiment analysis methodology -- Chapter 6. Analysis of online social networks for the identification of sarcasm -- Chapter 7. A novel algorithm for sentiment analysis of online movie reviews -- Chapter 8. Authorship attribution for online social media -- Chapter 9. Business-oriented analytics with social network of things -- Chapter 10. Social aware cognitive radio networks: effectiveness of social networks as a strategic tool for organizational business management -- Chapter 11. An experimental evaluation of link prediction for movie suggestions using social media content -- Chapter 12. Knowledge discovery using data stream mining: an analytical approach -- Chapter 13. Trust and credibility analysis of websites: role of trust and credibility in evaluating online content.

Restricted to subscribers or individual electronic text purchasers.

"This book addresses different aspects such as sentiment analyzing with sarcasm detection, issues in data consolidation, and various challenges with dependability and trust analytics, automation of content extraction and an assortment of applications of business applications in social media analytics using machine learning, evolutionary algorithms and other techniques"--

ISBN: 9781522550983 (ebook)Subjects--Topical Terms:

337142
Online social networks.

LC Class. No.: HM742 / .S62867 2018e

Dewey Class. No.: 302.30285

Social network analytics for contemporary business organizations[electronic resource] /
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245 0 0 $a Social network analytics for contemporary business organizations $h [electronic resource] / $c Himani Bansal, Guishan Shrivastava, Gia Nhu Nguyen and Loredana-Mihaela Stanciu, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xviii, 321 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Social network analysis: tools, techniques, and technologies -- Chapter 2. Social networking data analysis tools and services -- Chapter 3. Social implications of e-government -- Chapter 4. Thwarting spam on Facebook: identifying spam posts using machine learning techniques -- Chapter 5. Impact of sarcasm in sentiment analysis methodology -- Chapter 6. Analysis of online social networks for the identification of sarcasm -- Chapter 7. A novel algorithm for sentiment analysis of online movie reviews -- Chapter 8. Authorship attribution for online social media -- Chapter 9. Business-oriented analytics with social network of things -- Chapter 10. Social aware cognitive radio networks: effectiveness of social networks as a strategic tool for organizational business management -- Chapter 11. An experimental evaluation of link prediction for movie suggestions using social media content -- Chapter 12. Knowledge discovery using data stream mining: an analytical approach -- Chapter 13. Trust and credibility analysis of websites: role of trust and credibility in evaluating online content.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book addresses different aspects such as sentiment analyzing with sarcasm detection, issues in data consolidation, and various challenges with dependability and trust analytics, automation of content extraction and an assortment of applications of business applications in social media analytics using machine learning, evolutionary algorithms and other techniques"-- $c Provided by publisher.
650 0 $a Online social networks. $3 337142
650 0 $a Social sciences $x Network analysis. $3 418981
650 0 $a Data mining. $3 337740
650 0 $a Computational linguistics. $3 181986
700 1 $a Bansal, Himani, $d 1985- $e editor. $3 732992
700 1 $a Shrivastava, Gulshan, $d 1987- $e editor. $3 732993
700 1 $a Nguyen, Gia Nhu, $e editor. $3 732994
700 1 $a Stanciu, Loredana-Mihaela, $e editor. $3 732995
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5097-6