IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Deep Learning for Social Media Text Analytics

Deep Learning for Social Media Text Analytics
View Sample PDF
Author(s): Anto Arockia Rosaline R. (Department of Information Technology, Rajalakshmi Engineering College, Chennai, India)and Parvathi R. (School of Computer Science and Engineering, VIT University, Chennai, India)
Copyright: 2022
Pages: 20
Source title: Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch043

Purchase

View Deep Learning for Social Media Text Analytics on the publisher's website for pricing and purchasing information.

Abstract

Text analytics is the process of extracting high quality information from the text. A set of statistical, linguistic, and machine learning techniques are used to represent the information content from various textual sources such as data analysis, research, or investigation. Text is the common way of communication in social media. The understanding of text includes a variety of tasks including text classification, slang, and other languages. Traditional Natural Language Processing (NLP) techniques require extensive pre-processing techniques to handle the text. When a word “Amazon” occurs in the social media text, there should be a meaningful approach to find out whether it is referring to forest or Kindle. Most of the time, the NLP techniques fail in handling the slang and spellings correctly. Messages in Twitter are so short such that it is difficult to build semantic connections between them. Some messages such as “Gud nite” actually do not contain any real words but are still used for communication.

Related Content

. © 2023. 34 pages.
. © 2023. 15 pages.
. © 2023. 15 pages.
. © 2023. 18 pages.
. © 2023. 24 pages.
. © 2023. 32 pages.
. © 2023. 21 pages.
Body Bottom