Computational Intelligence Applications for Text and Sentiment Data Analysis

The book Computational Intelligence Applications for Text and Sentiment Data Analysis explores the latest advances in text information processing and data analysis technologies, focusing on sentiment analysis from multifaceted data. It investigates challenges such as identifying subjective information, identifying sentiment polarity, and domain dependency, as well as spam and fake news detection, short abbreviation, sarcasm, word negation, and word ambiguity. It also looks at the process of extracting sentiment from different multimodal information and semantic concepts.

Format: Paperback / softback
Length: 270 pages
Publication date: 01 August 2023
Publisher: Elsevier Science & Technology

Computational Intelligence Applications for Text and Sentiment Data Analysis delves into the cutting-edge advancements in text information processing and data analysis technologies, with a specific emphasis on sentiment analysis from diverse data sources. The book explores a wide array of challenges associated with accurately analyzing online sentiments, encompassing the identification of subjective information from text, the differentiation of sentiment polarity, and the consideration of domain dependencies. It also examines the detection of spam and fake news, the recognition of short abbreviations, sarcasm, word negation, and various forms of word ambiguity. Furthermore, the book explores the intricate process of extracting sentiment from various multimodal information, including audio, video, and text, as well as semantic concepts.

In each chapter, the authors of the book delve into the role of computational intelligence techniques, such as deep learning, convolutional neural networks, fuzzy and rough set, global optimizers, and hybrid machine learning techniques, in addressing the inherent problems of sentiment analysis applications. These techniques are employed to enhance the accuracy, efficiency, and scalability of sentiment analysis systems, enabling them to handle large volumes of text data and extract meaningful insights from diverse perspectives.

By leveraging the power of computational intelligence, the book provides a comprehensive and practical guide for researchers, practitioners, and industry professionals seeking to leverage text and sentiment data for various applications, including social media analysis, customer feedback analysis, market research, and healthcare informatics. It serves as a valuable resource for those looking to stay updated with the latest developments and best practices in this rapidly evolving field.

Weight: 456g
Dimension: 151 x 230 x 27 (mm)
ISBN-13: 9780323905350