Computational Intelligence Applications for Text and Sentiment Data Analysis

Dipankar Das editor Abhishek Basu editor Anup Kumar Kolya editor Soham Sarkar editor

Format:Paperback

Publisher:Elsevier Science & Technology

Published:20th Jul '23

Should be back in stock very soon

Computational Intelligence Applications for Text and Sentiment Data Analysis cover

Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specifically focusing on sentiment analysis from multifaceted data. The book investigates a wide range of challenges involved in the accurate analysis of online sentiments, including how to i) identify subjective information from text, i.e., exclusion of ‘neutral’ or ‘factual’ comments that do not carry sentiment information, ii) identify sentiment polarity, and iii) domain dependency. Spam and fake news detection, short abbreviation, sarcasm, word negation, and a lot of word ambiguity are also explored. Further chapters look at the difficult process of extracting sentiment from different multimodal information (audio, video and text), semantic concepts. In each chapter, the book's authors explore how computational intelligence (CI) techniques, such as deep learning, convolutional neural network, fuzzy and rough set, global optimizers, and hybrid machine learning techniques play an important role in solving the inherent problems of sentiment analysis applications.

ISBN: 9780323905350

Dimensions: unknown

Weight: 450g

270 pages