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Big Data Analytics in Cognitive Social Media and Literary Texts

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Cover of 'Big Data Analytics in Cognitive Social Media and Literary Texts'

Table of Contents

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    Book Overview
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    Chapter 1 The Concept of Cognitive Social Media and Cognitive Literary Studies
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    Chapter 2 Big Data Analytics for Market Prediction via Consumer Insight
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    Chapter 3 Deconstructive Big Data Analytics: Literary Texts Analysis Through Atlas.ti Software
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    Chapter 4 Study of Big Data Analytics Tool: Apache Spark
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    Chapter 5 Contemporary Social Media and IoT-Based Pandemic Control: Exploring Possibilities of Big Data Analytics for Healthcare Governance
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    Chapter 6 Analyzing Women Health-Related Quality of Life Using Sentiment Analysis on Social Media
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    Chapter 7 Necessity of Big Data Analytics in Social Media for Questioning the Existence and Survival of Women and the Marginalized People
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    Chapter 8 Big Data Analytics and Cybersecurity: Emerging Trends
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    Chapter 9 Seizing the Networked Crime: Legal Framework for the Governance of Social Media Crimes in India
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    Chapter 10 Toxic Masculinity and Inherent Misogyny on Social Media: Preventive Laws and Indian Judicial Approach
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    Chapter 11 Quantifying Human Sentiments Using Qualitative Approach with Semantic-Sentiment Analysis
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    Chapter 12 Cognitive Transformation Through Social Media
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    Chapter 13 Understanding Digital Diaspora as Cognitive Social Media: Necessity of Big Data Analytics for Peace and Harmony
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    Chapter 14 Data Analytics of Psychological Distress and Coping Among Fresh Migrant from North Eastern Region to Bengaluru City
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    Chapter 15 Security and Privacy Challenges for Big Data on Social Media
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    Chapter 16 Social Media: The Dark Horse of Market in Consumer Decision Journey
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Title
Big Data Analytics in Cognitive Social Media and Literary Texts
Published by
Springer Singapore, January 2021
DOI 10.1007/978-981-16-4729-1
ISBNs
978-9-81-164728-4, 978-9-81-164729-1
Editors

Sanjiv Sharma, Valiur Rahaman, G. R. Sinha

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 13%
Student > Bachelor 1 7%
Professor > Associate Professor 1 7%
Unspecified 1 7%
Researcher 1 7%
Other 1 7%
Unknown 8 53%
Readers by discipline Count As %
Arts and Humanities 1 7%
Unspecified 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Business, Management and Accounting 1 7%
Linguistics 1 7%
Other 2 13%
Unknown 8 53%