| Computational Methods for Affect Detection from Natural Language 2021 Edition Contributor(s): Balahur-Dobrescu, Alexandra (Author), Taboada, Maite (Author), Schuller, Björn W. (Author) |
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ISBN: 3319006010 ISBN-13: 9783319006017 Publisher: Springer OUR PRICE: $94.99 Product Type: Hardcover Published: August 2024 This item may be ordered no more than 25 days prior to its publication date of August 11, 2024 |
| Additional Information |
| BISAC Categories: - Computers | Natural Language Processing - Language Arts & Disciplines | Linguistics - General - Technology & Engineering | Telecommunications |
| Dewey: 006.35 |
| Series: Computational Social Sciences |
| Physical Information: 250 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: A broad overview of natural language processing in affective computing is given by this title. Its goal is to familiarize the reader with current approaches in affective computing as well as the most relevant concepts related to this field (affect, sentiment, subjectivity and others). Research in human affect has a long established tradition in social sciences - Philosophy, Psychology, Socio-psychology, Cognitive Science, Pragmatics, Marketing, Communication. The study of affect from a computational point of view is a recent field in Artificial Intelligence, denominated "Affective Computing". Despite the novelty of the subject, the volume and importance of research in automatic human affect recognition, classification and simulation has been constantly growing in the past decades, leading to the development of further sub-areas of research. One of these directions deals with the study of automatic affect treatment from text, in the Artificial Intelligence area of Natural Language Processing. In this context, different tasks have been developed, from emotion detection, subjectivity analysis, opinion mining to sentiment analysis and appraisal analysis. |