Authors:
- Broadens understanding of multimodal sentiment analysis
- Presents a summary of the relevant state of the art
- Contains key visualizations
Part of the book series: Socio-Affective Computing (SAC, volume 8)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions.
Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer.
This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion.
The inclusion of key visualization and case studies will enable readers to understand better these approaches.
Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.Reviews
Authors and Affiliations
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Artificial Intelligence Initiative, ASTAR, Singapore, Singapore
Soujanya Poria
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Computing Science and Mathematics, University of Stirling, Stirling, UK
Amir Hussain
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School of Computer Engineering, Nanyang Technological University, Singapore, Singapore
Erik Cambria
Bibliographic Information
Book Title: Multimodal Sentiment Analysis
Authors: Soujanya Poria, Amir Hussain, Erik Cambria
Series Title: Socio-Affective Computing
DOI: https://doi.org/10.1007/978-3-319-95020-4
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-95018-1Published: 03 November 2018
Softcover ISBN: 978-3-030-06956-8Published: 28 December 2018
eBook ISBN: 978-3-319-95020-4Published: 24 October 2018
Series ISSN: 2509-5706
Series E-ISSN: 2509-5714
Edition Number: 1
Number of Pages: XI, 214
Number of Illustrations: 9 b/w illustrations, 25 illustrations in colour
Topics: Neurosciences, Multimedia Information Systems, Image Processing and Computer Vision, Natural Language Processing (NLP), Translation