Advances In Sentiment Analysis
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Advances in Sentiment Analysis
This cutting-edge book brings together experts in the field to provide a multidimensional perspective on sentiment analysis, covering both foundational and advanced methodologies. Readers will gain insights into the latest natural language processing and machine learning techniques that power sentiment analysis, enabling the extraction of nuanced emotions from text. Key Features: •State-of-the-Art Techniques: Explore the most recent advancements in sentiment analysis, from deep learning approaches to sentiment lexicons and beyond. •Real-World Applications: Dive into a wide range of applications, including social media monitoring, customer feedback analysis, and sentiment-driven decision-making. •Cross-Disciplinary Insights: Understand how sentiment analysis influences and is influenced by fields such as marketing, psychology, and finance. •Ethical and Privacy Considerations: Delve into the ethical challenges and privacy concerns inherent to sentiment analysis, with discussions on responsible AI usage. •Future Directions: Get a glimpse into the future of sentiment analysis, with discussions on emerging trends and unresolved challenges. This book is an essential resource for researchers, practitioners, and students in fields like natural language processing, machine learning, and data science. Whether you’re interested in understanding customer sentiment, monitoring social media trends, or advancing the state of the art, this book will equip you with the knowledge and tools you need to navigate the complex landscape of sentiment analysis.
Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
Author: Suman Kumar Swarnkar
language: en
Publisher: Springer Nature
Release Date: 2025-07-23
This open access volume presents select proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025). It covers AI fundamentals, machine learning, deep learning, NLP, computer vision, robotics, and ethical AI. Key application areas include healthcare, industry automation, smart cities, agriculture, education, cybersecurity, and business.
Advances in Intelligent Systems and Digital Applications
This book serves as a comprehensive reference, providing cutting-edge knowledge on intelligent systems and digital applications. It covers theoretical foundations and significant issues in machine learning, deep learning, and data analytics. Each chapter concludes with a detailed bibliography for further in-depth reading.Divided into two sections—Foundations and Applications—the book offers a complete source of information on its theme. The chapters include concepts, algorithms, figures, graphs, and tables to enhance readability. The target audience includes researchers, practitioners, and postgraduate and graduate students developing or utilizing artificial intelligence algorithms in various applications.