[Valiur Rahaman (he/his/him)]

We are editing the book “Big Data Analytics in Cognitive Social Media and Literary Text: Theory and Praxis” to be published by Springer. As the book editors, we commission suitable authors to contribute chapters to the book. In this regard, we are glad to invite you and your co-research partners/colleagues consider contributing a chapter. The book would cover (but not limited to):

<li style=”font-weight: 400;”>Semantic Supplementation of Big Data & Big Data Analytics
<li style=”font-weight: 400;”>Big Data Analytics for Market Predictions and Design Predictions
<li style=”font-weight: 400;”>Big Data Analytics, Cognitive Science & Social Media
<li style=”font-weight: 400;”>Concepts of Social Structure & Stratification in 21st-century terms
<li style=”font-weight: 400;”>Big data analysis of legal awareness and unknown criminal mindset
<li style=”font-weight: 400;”>Concepts and Distortions in Media, Social Media
<li style=”font-weight: 400;”>Social Media & Cognitive Social Media: Theory & Praxis
<li style=”font-weight: 400;”>Big Data Analytics in behaviour Predictions through platforms of social media,
<li style=”font-weight: 400;”>Connection of cognition with Social Media & Para-media, Media Prediction,
<li style=”font-weight: 400;”>Social Media & Cognitive Social Media.
<li style=”font-weight: 400;”>The Networked crimes, cyber-crime and the question of digital litigation
<li style=”font-weight: 400;”>Social Structure through human communication & social media
<li style=”font-weight: 400;”>Compulsive Disorders representation through Social Networking,
<li style=”font-weight: 400;”>Application of Social Cognitive Theory to develop a computational model for behaviour analysis
<li style=”font-weight: 400;”>Implications of ageing reflection through social media, influence of social structure
<li style=”font-weight: 400;”>Big Data Analysis in Quantifying problems of social structures
<li style=”font-weight: 400;”>Practising Semantic analysis & Quantifying Human Sentiments
<li style=”font-weight: 400;”>Application of big data analytics in text mining: Case Studies of Archiving the Literary World
<li style=”font-weight: 400;”>Possibilities of Digital representation of literary text, text mining
<li style=”font-weight: 400;”>Computational corpus of complex literary arts,
<li style=”font-weight: 400;”>Big Data to challenge distortions of prophetic Books through computational tools
<li style=”font-weight: 400;”>Deconstruction in Digital Humanities practices/Speculative Humanities
<li style=”font-weight: 400;”>Atlas.ti as a Big Data Tool for Qualitative Research in Social Media
<li style=”font-weight: 400;”>Big Data and Corpus Making Literary Text Analysis through R and Python
<li style=”font-weight: 400;”>SpecLab Case Studies

Your contribution should be up to 25 pages (around 1000 words) and we encourage the inclusion of quality images and even enhanced features such as animated figures. Do let us know if you are willing to contribute and provide an outline (abstract) of your tentative chapter by 12th June 2020.
The detailed “Call for Chapters” can be seen at https://cfc-springer-big-data.github.io/publication_springer_cfc_big_data_analytics/
Please take care and stay safe!

Interested authors/researchers are encouraged to submit full chapter by 31st July 2020

The Editors

 

[Author]

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