Big Data Analytics in Cognitive Social Media and Literary Texts : Theory and Praxis /

This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on k...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Sharma, Sanjiv (Editor), Rahaman, Valiur (Editor), Sinha, G. R. (Editor)
Format: eBook
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media and communication studies and computational/digital humanities.
Physical Description:1 online resource (XXIX, 300 pages 189 illustrations, 134 illustrations in color.)
ISBN:9789811647291
DOI:10.1007/978-981-16-4729-1