Overview
- Offers a broad overview of natural language processing in affective computing
- Familiarizes readers with current approaches in affective computing with explanations of theory as well as practical examples
- Introduces and defines the concepts employed in the computational treatment of affect from text, from an inter-disciplinary, unified perspective
- A timely topic for the age of social media
Part of the book series: Computational Social Sciences (CSS)
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Keywords
- Affect in AI
- Affective Computing
- Emotion Detection
- Multilingual Sentiment Analysis
- Multilinguality
- Opinion Mining
- Opinion Trend Analysis
- Sentiment Analysis
- Social Media Analysis
- Subjectivity Analysis
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Computational Methods for Affect Detection from Natural Language
Authors: Alexandra Balahur-Dobrescu, Maite Taboada, Björn W. Schuller
Series Title: Computational Social Sciences
Publisher: Springer Cham
eBook Packages: Education, Education (R0)
Copyright Information: Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-319-00601-7Due: 11 August 2024
eBook ISBN: 978-3-319-00602-4Due: 11 August 2024
Series ISSN: 2509-9574
Series E-ISSN: 2509-9582
Edition Number: 1
Number of Pages: 250