大葉大學圖書館 |

Advances in social media analysis[electronic resource] /

Record Type:	Language materials, printed : Monograph/item
[NT 15000414]:	006.312
Title/Author:	Advances in social media analysis/ edited by Mohamed Medhat Gaber ... [et al.].
other author:	Gaber, Mohamed Medhat.
Published:	Cham : : Springer International Publishing :, 2015.
Description:	vii, 151 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
Subject:	Data mining.
Subject:	Social media.
Subject:	User-generated content.
Subject:	Engineering.
Subject:	Computational Intelligence.
Subject:	Artificial Intelligence (incl. Robotics)
ISBN:	9783319184586 (electronic bk.)
ISBN:	9783319184579 (paper)
[NT 15000228]:	Case-Studies in Mining User-Generated Reviews for Recommendation -- Mining Newsworthy Topics from Social Media -- Sentiment Analysis Using Supervised Learning with Domain-Adaptation and Sentence-Based Analysis -- Pattern-based Emotion Classification on Social Media -- Entity-based Opinion Mining from Text and Multimedia -- Predicting Emotion Labels for Chinese Microblog Texts.
[NT 15000229]:	This volume presents a collection of carefully selected contributions in the area of social media analysis. Each chapter opens up a number of research directions that have the potential to be taken on further in this rapidly growing area of research. The chapters are diverse enough to serve a number of directions of research with Sentiment Analysis as the dominant topic in the book. The authors have provided a broad range of research achievements from multimodal sentiment identification to emotion detection in a Chinese microblogging website. The book will be useful to research students, academics and practitioners in the area of social media analysis.
Online resource:	http://dx.doi.org/10.1007/978-3-319-18458-6

Advances in social media analysis[electronic resource] /
Advances in social media analysis[electronic resource] /edited by Mohamed Medhat Gaber ... [et al.]. - Cham :Springer International Publishing :2015. - vii, 151 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.6021860-949X ;. - Studies in computational intelligence ;v.379..

Case-Studies in Mining User-Generated Reviews for Recommendation -- Mining Newsworthy Topics from Social Media -- Sentiment Analysis Using Supervised Learning with Domain-Adaptation and Sentence-Based Analysis -- Pattern-based Emotion Classification on Social Media -- Entity-based Opinion Mining from Text and Multimedia -- Predicting Emotion Labels for Chinese Microblog Texts.

This volume presents a collection of carefully selected contributions in the area of social media analysis. Each chapter opens up a number of research directions that have the potential to be taken on further in this rapidly growing area of research. The chapters are diverse enough to serve a number of directions of research with Sentiment Analysis as the dominant topic in the book. The authors have provided a broad range of research achievements from multimodal sentiment identification to emotion detection in a Chinese microblogging website. The book will be useful to research students, academics and practitioners in the area of social media analysis.

ISBN: 9783319184586 (electronic bk.)

Standard No.: 10.1007/978-3-319-18458-6doiSubjects--Topical Terms:

337740
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Advances in social media analysis[electronic resource] /
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245 0 0 $a Advances in social media analysis $h [electronic resource] / $c edited by Mohamed Medhat Gaber ... [et al.].
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505 0 $a Case-Studies in Mining User-Generated Reviews for Recommendation -- Mining Newsworthy Topics from Social Media -- Sentiment Analysis Using Supervised Learning with Domain-Adaptation and Sentence-Based Analysis -- Pattern-based Emotion Classification on Social Media -- Entity-based Opinion Mining from Text and Multimedia -- Predicting Emotion Labels for Chinese Microblog Texts.
520 $a This volume presents a collection of carefully selected contributions in the area of social media analysis. Each chapter opens up a number of research directions that have the potential to be taken on further in this rapidly growing area of research. The chapters are diverse enough to serve a number of directions of research with Sentiment Analysis as the dominant topic in the book. The authors have provided a broad range of research achievements from multimodal sentiment identification to emotion detection in a Chinese microblogging website. The book will be useful to research students, academics and practitioners in the area of social media analysis.
650 0 $a Data mining. $3 337740
650 0 $a Social media. $3 350802
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700 1 $a Gaber, Mohamed Medhat. $3 512188
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950 $a Engineering (Springer-11647)