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Advances in Social Media Analysis [electronic resource] / edited by Mohamed Medhat Gaber, Mihaela Cocea, Nirmalie Wiratunga, Ayse Goker.

Contributor(s): Gaber, Mohamed Medhat [editor.] | Cocea, Mihaela [editor.] | Wiratunga, Nirmalie [editor.] | Goker, Ayse [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 602Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: VII, 151 p. 29 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319184586.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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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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.  .

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