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Affective Computing and Sentiment Analysis: Emotion, Metaphor and Terminology de Khurshid Ahmad

Affective Computing and Sentiment Analysis: Emotion, Metaphor and Terminology: Text, Speech and Language Technology, cartea 45

Editat de Khurshid Ahmad
en Limba Engleză Paperback – 19 noi 2013
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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Specificații

ISBN-13: 9789400737884
ISBN-10: 9400737882
Pagini: 164
Ilustrații: XIV, 150 p.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.24 kg
Ediția:2011
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Text, Speech and Language Technology

Locul publicării:Dordrecht, Netherlands

Public țintă

Research

Cuprins

Introduction: Affect Computing and Sentiment Analysis. References.- 1. Understanding Metaphors: The Paradox of Unlike Things Compared by Sam Glucksberg.- 2. Metaphor as Resources for the Conceptualisation and Expression of Emotion by Andrew Goatly.- 3. The Deep Lexical Semantics of Emotions by Jerry R. Hobbs and Andrew Gordon.- 4. Genericity and Metaphoricity Both Involve Sense Modulation by Carl Vogel.- 5. Affect Transfer by Metaphor for an Intelligent Conversational Agent by Alan Wallington, Rodrigo Agerri, John Barnden, Mark Lee and Tim Rumbell.- 6. Detecting Uncertainty in Spoken Dialogues: An Explorative Research for the Automatic Detection of Speaker Uncertainty by Using Prosodic Markers by Jeroen Dral, Dirk Heylen and Rieks op den Akker.- 7. Metaphors and Metaphor-like Processes Across Languages: Notes on English and Italian Language of Economics by Maria Teresa Musacchio.- 8. The ‘Return’ and ‘Volatility’ of Sentiments: An Attempt to Quantify the Behaviour of the Markets? byKhurshid Ahmad.- 9 Sentiment Analysis Using Automatically Labelled Financial News Items by Michel Généreux, Thierry Poibeau and Moshe Koppel.- 10 Co-Word Analysis for Assessing Consumer Associations: A Case Study in Market Research by Thorsten Teichert, Gerhard Heyer, Katja Schöntag and Patrick Mairif.- 11 Automating Opinion Analysis in Film Reviews: The Case of Statistic Versus Linguistic Approach by Damien Poirier, Cécile Bothorel, Émilie Guimier De Neef, and Marc Boullé.- Afterword: ‘The Fire Sermon’ by Yorick Wilks. References. 

Textul de pe ultima copertă

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. 

Caracteristici

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