Affective Computing and Sentiment Analysis

Emotion, Metaphor and Terminology

  • Khurshid Ahmad

Part of the Text, Speech and Language Technology book series (TLTB, volume 45)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Jerry R. Hobbs, Andrew S. Gordon
    Pages 27-34
  3. Alan Wallington, Rodrigo Agerri, John Barnden, Mark Lee, Tim Rumbell
    Pages 53-66
  4. Michel Généreux, Thierry Poibeau, Moshe Koppel
    Pages 101-114
  5. Thorsten Teichert, Gerhard Heyer, Katja Schöntag, Patrick Mairif
    Pages 115-124
  6. Damien Poirier, Cécile Bothorel, Émilie Guimier De Neef, Marc Boullé
    Pages 125-140
  7. Back Matter
    Pages 141-148

About this book


This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect – including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally.  Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated.

This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology. 


homeland security human computer interaction information extraction knowledge management sentiment analysis text corpora

Editors and affiliations

  • Khurshid Ahmad
    • 1
  1. 1.Department of Computer ScienceTrinity CollegeDublin 2Ireland

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