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Book synopsis

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. 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 and systems.

Book details

Book category Books in English Mathematics & science Biology, life sciences Life sciences: general issues

• Full title: Sentic Computing
• Subtitle: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
• Author: Erik Cambria, Amir Hussain
• Language: English
• Binding: Paperback
• Number of pages: 176
• EAN: 9783319795164
• ID: 21072524
• Publisher: Springer International Publishing AG
• Weight: 424 g
• Dimensions: 235 × 155 × 10 mm
• Published: 2017

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