Overview
- First approach to sentiment analysis that merges AI, linguistics, and psychology
- Comprehensive explanation of popular sentic computing techniques
- Full set of linguistic patterns for sentiment analysis
- Downloadable knowledge base
Part of the book series: Socio-Affective Computing (SAC, volume 1)
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About this book
This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web.
Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain.
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Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed:
•   Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference
•   Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text
•   Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses
This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction andsystems.
Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain.
Â
Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed:
•   Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference
•   Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text
•   Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses
This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction andsystems.
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Table of contents (5 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Sentic Computing
Book Subtitle: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
Authors: Erik Cambria, Amir Hussain
Series Title: Socio-Affective Computing
DOI: https://doi.org/10.1007/978-3-319-23654-4
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2015
Hardcover ISBN: 978-3-319-23653-7Published: 18 December 2015
Softcover ISBN: 978-3-319-79516-4Published: 21 March 2019
eBook ISBN: 978-3-319-23654-4Published: 11 December 2015
Series ISSN: 2509-5706
Series E-ISSN: 2509-5714
Edition Number: 1
Number of Pages: XXII, 176
Number of Illustrations: 14 b/w illustrations, 40 illustrations in colour
Topics: Neurosciences, Data Mining and Knowledge Discovery, Semantics, Cognitive Psychology