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This volume synthesises research and development in cognitive science and computing that deal with the automated assessment of human emotion. Affect computing systems are used in identifying terror threats, and are extensively used in marketing and finance. This volume comprises affect computing systems that learn to identify sentiment bearing sentences, and help in evaluating the polarity of opinion, positive/negative , in written text and speech.

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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.

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