Multimodal Sentiment Analysis

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.
1133095258
Multimodal Sentiment Analysis

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.
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Multimodal Sentiment Analysis

Multimodal Sentiment Analysis

Multimodal Sentiment Analysis

Multimodal Sentiment Analysis

Overview

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.

Product Details

ISBN-13: 9783319950204
Publisher: Springer-Verlag New York, LLC
Publication date: 10/24/2018
Series: Socio-Affective Computing , #8
Sold by: Barnes & Noble
Format: eBook
File size: 11 MB
Note: This product may take a few minutes to download.

Table of Contents

Preface.- Introduction and Motivation.- Background.- Literature Survey and Datasets.- Concept Extraction from Natural Text for Concept Level Text Analysis.- EmoSenticSpace: Dense concept-based affective features with common-sense knowledge.- Sentic Patterns: Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns.- Combining Textual Clues with Audio-Visual Information for Multimodal Sentiment Analysis.- Conclusion and Future Work.- Index.

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