Advances in Social Media Analysis
Advances in Social Media Analysis
edited by Mohamed Medhat Gaber, Mihaela Cocea, Nirmalie Wiratunga, Ayse Goker.
- 1 recurso en línea (VII, 151 páginas 29 ilustraciones)
- Studies in Computational Intelligence, 602 1860-949X ; Engineering (Springer-11647) .
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. .
9783319184586
10.1007/978-3-319-18458-6 doi
Data mining
QA76.9.D343 / 2015 EB
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. .
9783319184586
10.1007/978-3-319-18458-6 doi
Data mining
QA76.9.D343 / 2015 EB