Skip to main content

Computational Intelligence Applications for Text and Sentiment Data Analysis

  • 1st Edition - July 14, 2023
  • Editors: Dipankar Das, Anup Kumar Kolya, Abhishek Basu, Soham Sarkar
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 3 2 3 - 9 0 5 3 5 - 0
  • eBook ISBN:
    9 7 8 - 0 - 3 2 3 - 9 0 6 3 7 - 1

Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specif… Read more

Computational Intelligence Applications for Text and Sentiment Data Analysis

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code needed.

Image of books

Institutional subscription on ScienceDirect

Request a sales quote
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.