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Social multimedia signals = signal p...

Roy, Suman Deb.

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Social multimedia signals = signal processing approach to social network phenomena /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Social multimedia signals/ by Suman Deb Roy, Wenjun Zeng.
Reminder of title:	signal processing approach to social network phenomena /
Author:	Roy, Suman Deb.
other author:	Zeng, Wenjun.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	x, 176 p. :ill., digital ;24 cm.
[NT 15003449]:	Web 2.x -- Media on the Web -- The World of Signals -- The Network and the Signal -- Detection - Needle in a Haystack -- Estimation - The Empirical Judgment -- Following Signal Trajectories -- Capturing Cross-Domain Ripples -- Socially-aware Media Applications -- Revelations from Social Multimedia Data -- Socio-Semantic Analysis -- Data Visualization: Gazing at Ripples.
Contained By:	Springer eBooks
Subject:	Multimedia communications. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-09117-4
ISBN:	9783319091174 (electronic bk.)

Social multimedia signals = signal processing approach to social network phenomena /
Roy, Suman Deb.

Social multimedia signalssignal processing approach to social network phenomena /[electronic resource] :by Suman Deb Roy, Wenjun Zeng. - Cham :Springer International Publishing :2015. - x, 176 p. :ill., digital ;24 cm.

Web 2.x -- Media on the Web -- The World of Signals -- The Network and the Signal -- Detection - Needle in a Haystack -- Estimation - The Empirical Judgment -- Following Signal Trajectories -- Capturing Cross-Domain Ripples -- Socially-aware Media Applications -- Revelations from Social Multimedia Data -- Socio-Semantic Analysis -- Data Visualization: Gazing at Ripples.

Social Multimedia Signals is intended for those whose interest is to study the Social Web and develop automated tools to analyze it better. It is especially useful for researchers experienced with signal processing or multimedia analysis but have little exposure to social networks and social multimedia data. Those new to social multimedia should find the first chapters extremely useful to get a thorough look at how social data behaves. Conversely, social scientists should find useful the authors' introduction to several signal processing techniques that can be employed to manipulate large-scale social data. For those new to signal processing, Chapters 5, 6 and 7 will get readers underway with basic techniques for signal processing from social multimedia. Later chapters include a significant amount of material on machine learning for those interested in intelligent algorithms for the Social Web. The authors wrote this book in a balanced fashion, for multimedia researchers, social scientists, network scientists, data scientists who work with social web data, and professionals who use social media on a daily basis. Explores how media popularity in one domain is determined by another domain; Presents a granular look at social networks: micro, meso, and macro; Examines finding hidden communities in social networks based on shared multimedia.

ISBN: 9783319091174 (electronic bk.)

Standard No.: 10.1007/978-3-319-09117-4doiSubjects--Topical Terms:

590562
Multimedia communications.

LC Class. No.: TK5105.15

Dewey Class. No.: 006.7

Social multimedia signals = signal processing approach to social network phenomena /
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245 1 0 $a Social multimedia signals $h [electronic resource] : $b signal processing approach to social network phenomena / $c by Suman Deb Roy, Wenjun Zeng.
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505 0 $a Web 2.x -- Media on the Web -- The World of Signals -- The Network and the Signal -- Detection - Needle in a Haystack -- Estimation - The Empirical Judgment -- Following Signal Trajectories -- Capturing Cross-Domain Ripples -- Socially-aware Media Applications -- Revelations from Social Multimedia Data -- Socio-Semantic Analysis -- Data Visualization: Gazing at Ripples.
520 $a Social Multimedia Signals is intended for those whose interest is to study the Social Web and develop automated tools to analyze it better. It is especially useful for researchers experienced with signal processing or multimedia analysis but have little exposure to social networks and social multimedia data. Those new to social multimedia should find the first chapters extremely useful to get a thorough look at how social data behaves. Conversely, social scientists should find useful the authors' introduction to several signal processing techniques that can be employed to manipulate large-scale social data. For those new to signal processing, Chapters 5, 6 and 7 will get readers underway with basic techniques for signal processing from social multimedia. Later chapters include a significant amount of material on machine learning for those interested in intelligent algorithms for the Social Web. The authors wrote this book in a balanced fashion, for multimedia researchers, social scientists, network scientists, data scientists who work with social web data, and professionals who use social media on a daily basis. Explores how media popularity in one domain is determined by another domain; Presents a granular look at social networks: micro, meso, and macro; Examines finding hidden communities in social networks based on shared multimedia.
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