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Advances in social media analysis

Gaber, Mohamed Medhat.

Advances in social media analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in social media analysisedited by Mohamed Medhat Gaber ... [et al.].
其他作者:	Gaber, Mohamed Medhat.
出版者:	Cham :Springer International Publishing :2015.
面頁冊數:	vii, 151 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Data mining.
電子資源:	http://dx.doi.org/10.1007/978-3-319-18458-6
ISBN:	9783319184586 (electronic bk.)

Advances in social media analysis
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. 216..

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:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Advances in social media analysis
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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.
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