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Affective Computing and Sentiment Analysis

Emotion, Metaphor and Terminology

  • Book
  • © 2011

Overview

  • Intellectual Challenge: Research on sentiment analysis is rooted in the ancient arts of hermeneutics and linguistic philosophy
  • Academic Relevance: Sentiment analysis is exemplar qualitative analysis that has been automated
  • Semantic Web : Sentiment analysis is key to ‘intelligent’ search and retrieval especially in the mission critical area of surveillance and law & order
  • Financial Reward: Sentiment analysis is the missing link between fundamental analysis and technical analysis for financial markets

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

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Table of contents (11 chapters)

Keywords

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. 

Editors and Affiliations

  • Department of Computer Science, Trinity College, Dublin 2, Ireland

    Khurshid Ahmad

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