Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis (Socio-Affective Computing, 1)

Cambria, Erik,Hussain, Amir

ISBN 10: 3319236539 / ISBN 13: 9783319236537

Published by Springer, 2015

About this Item

Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_367917792

Bibliographic Details

Title: Sentic Computing: A Common-Sense-Based ...

Publisher: Springer

Publication Date: 2015

Binding: hardcover

Condition: Good

About this title

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 andsystems.