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The SenticNet Sentiment Lexicon: Exploring Semantic Richness in Multi-Word Concepts

  • Raoul¬†Biagioni

Part of the SpringerBriefs in Cognitive Computation book series (BRIEFSCC, volume 4)

Table of contents

  1. Front Matter
    Pages i-vi
  2. Raoul Biagioni
    Pages 1-6
  3. Raoul Biagioni
    Pages 7-16
  4. Raoul Biagioni
    Pages 17-31
  5. Raoul Biagioni
    Pages 33-43
  6. Raoul Biagioni
    Pages 45-50
  7. Raoul Biagioni
    Pages 51-53
  8. Back Matter
    Pages 55-55

About this book

Introduction

The research and its outcomes presented in this book, is about lexicon-based sentiment analysis. It uses single-, and multi-word concepts from the SenticNet sentiment lexicon as the source of sentiment information for the purpose of sentiment classification.

In 6 chapters the book sheds light on the comparison of sentiment classification accuracy between single-word and multi-word concepts, for which a bespoke sentiment analysis system developed by the author was used.

This book will be of interest to students, educators and researchers in the field of Sentic Computing.

Keywords

concepts polarity semantic richness sentiment analysis sentiment lexicon

Authors and affiliations

  • Raoul¬†Biagioni
    • 1
  1. 1.Dublin Institute of TechnologyDublin 6Ireland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-38971-4
  • Copyright Information The Author(s) 2016
  • Publisher Name Springer, Cham
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-3-319-38970-7
  • Online ISBN 978-3-319-38971-4
  • Series Print ISSN 2212-6023
  • Series Online ISSN 2212-6031
  • Buy this book on publisher's site
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