Sentimental Analysis and Deep Learning: Proceedings of ICSADL 2021

This book discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications, focusing on understanding human emotions and perceptions from user-generated data.

Format: Paperback / softback
Length: 1030 pages
Publication date: 26 October 2021
Publisher: Springer Verlag, Singapore

The book titled "Advances in Sentiment Analysis and Deep Learning: Selected Papers from ICSADL 2021" serves as a comprehensive compilation of papers presented at the International Conference on Sentimental Analysis and Deep Learning (ICSADL 2021), which was jointly organized by Tribhuvan University, Nepal; Prince of Songkla University, Thailand; and Ejesra during June 18th and 19th, 2021. This volume explores cutting-edge research endeavors focused on integrating artificial intelligence models, particularly deep learning techniques, into intelligent sentiment analysis applications. Emotions and sentiments have gained immense importance as key human factors in understanding the rich user-generated semantics and perceptions derived from the vast expanse of user-generated data. In this context, sentiment analysis emerges as a groundbreaking technology capable of automatically analyzing human emotions within data-driven applications. By leveraging sentiment analysis, businesses can effectively automate their processes and gain valuable insights from the vast unstructured data available.

Furthermore, deep learning emerges as a revolutionary paradigm, characterized by its extensive data-driven representation learning architectures. This book delves into all theoretical aspects of sentimental analysis, deep learning, and related topics, providing a comprehensive understanding of these fields.

The conference brought together experts from around the world to discuss the latest advancements in sentiment analysis and deep learning, fostering a collaborative environment for researchers, practitioners, and industry professionals to exchange ideas and share their expertise. The selected papers presented in this book represent the state-of-the-art research in these areas, covering a wide range of topics such as emotion recognition, sentiment classification, opinion mining, and deep learning-based sentiment analysis models.

By compiling these papers, the book aims to provide a valuable resource for scholars, researchers, and practitioners interested in advancing the field of sentiment analysis and deep learning. It serves as a reference for those seeking to explore the latest techniques, applications, and challenges in these domains.

The book is organized into several chapters, each dedicated to a specific aspect of sentiment analysis and deep learning. The chapters are authored by leading researchers and experts in the field, ensuring the highest quality and relevance of the content.

In conclusion, "Advances in Sentiment Analysis and Deep Learning: Selected Papers from ICSADL 2021" is a must-read for anyone interested in the latest developments in sentiment analysis and deep learning. It offers a comprehensive overview of the state-of-the-art research, theoretical foundations, and practical applications in these fields. The book serves as a valuable resource for scholars, researchers, practitioners, and industry professionals seeking to advance their knowledge and expertise in these areas.

Weight: 1597g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811651564
Edition number: 1st ed. 2022