Sentic Computing

A Common-Sense-Based Framework for Concept-Level Sentiment Analysis

  • Erik Cambria
  • Amir Hussain
Part of the Socio-Affective Computing book series (SAC, volume 1)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Erik Cambria, Amir Hussain
    Pages 1-21
  3. Erik Cambria, Amir Hussain
    Pages 23-71
  4. Erik Cambria, Amir Hussain
    Pages 73-106
  5. Erik Cambria, Amir Hussain
    Pages 107-153
  6. Erik Cambria, Amir Hussain
    Pages 155-160
  7. Back Matter
    Pages 161-176

About this book

Introduction

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.

Keywords

common-sense reasoning concept-level analysis linguistic patterns sentic computing sentiment analysis

Authors and affiliations

  • Erik Cambria
    • 1
  • Amir Hussain
    • 2
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.Computing Science and MathematicsUniversity of StirlingStirlingUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-23654-4
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-3-319-23653-7
  • Online ISBN 978-3-319-23654-4
  • About this book