Affective Computing and Sentiment Analysis: Emotion, Metaphor and Terminology

Description

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. Front Matter....Pages i-xiv Understanding Metaphors: The Paradox of Unlike Things Compared....Pages 1-12 Metaphor as Resource for the Conceptualisation and Expression of Emotion....Pages 13-25 The Deep Lexical Semantics of Emotions....Pages 27-34 Genericity and Metaphoricity Both Involve Sense Modulation....Pages 35-51 Affect Transfer by Metaphor for an Intelligent Conversational Agent....Pages 53-66 Detecting Uncertainty in Spoken Dialogues: An Exploratory Research for the Automatic Detection of Speaker Uncertainty by Using Prosodic Markers....Pages 67-77 Metaphors and Metaphor-Like Processes Across Languages: Notes on English and Italian Language of Economics....Pages 79-88 The ‘Return’ and ‘Volatility’ of Sentiments: An Attempt to Quantify the Behaviour of the Markets?....Pages 89-99 Sentiment Analysis Using Automatically Labelled Financial News Items....Pages 101-114 Co-Word Analysis for Assessing Consumer Associations: A Case Study in Market Research....Pages 115-124 Automating Opinion Analysis in Film Reviews: The Case of Statistic Versus Linguistic Approach....Pages 125-140 Back Matter....Pages 141-148