Springer - Textual Emotion Classification Deep Learning Book

Explore the specialized field of socio-affective computing with this academic text from Springer. Textual Emotion Classification Using Deep Broad Learning provides a technical look at how machine learning models interpret human emotion within written text. This book is designed for readers interested in the intersection of computer science and affective computing. As artificial intelligence continues to evolve, understanding how systems process linguistic nuances becomes more important. This publication focuses on deep learning methodologies applied to textual data, offering a resource for those studying AI and machine learning. It serves as a targeted study for professionals and students working within the computing and internet sectors who need to understand the mechanics of emotion detection in digital text.