Computational Methods for Affect Detection from Natural Language
(Sprache: Englisch)
This book offers a broad overview of natural language processing in affective computing. It presents a theoretical and practical overview of key research topics dealing with the computational treatment of affect from text.
Erscheint am 11.08.2024
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Produktinformationen zu „Computational Methods for Affect Detection from Natural Language “
This book offers a broad overview of natural language processing in affective computing. It presents a theoretical and practical overview of key research topics dealing with the computational treatment of affect from text.
Klappentext zu „Computational Methods for Affect Detection from Natural Language “
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.
Inhaltsverzeichnis zu „Computational Methods for Affect Detection from Natural Language “
Affect Computation from Text - Main Concepts and Tasks.- Subjectivity Analysis in Natural Language.- Sentiment Analysis.- Emotion Detection from Text.- Dealing with Multilinguality in Affect Computation from Text.- Applications of Affect Computation - Opinion Trend and Social Media Analysis.- Current Challenges and Envisaged Developments in Affect Computation from Text.
Bibliographische Angaben
- Autoren: Alexandra Balahur-Dobrescu , Maite Taboada , Björn W. Schuller
- 2024, 1st ed. 2024, 250 Seiten, Maße: 15,5 x 23,5 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3319006010
- ISBN-13: 9783319006017
- Erscheinungsdatum: 11.08.2024
Sprache:
Englisch
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