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Big data analytics in cognitive soci...

Rahaman, Valiur.

Big data analytics in cognitive social media and literary textstheory and praxis /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Big data analytics in cognitive social media and literary textsedited by Sanjiv Sharma, Valiur Rahaman, G. R. Sinha.
其他題名:	theory and praxis /
其他作者:	Sharma, Sanjiv.
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	xxix, 300 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	CognitionData processing.
電子資源:	https://doi.org/10.1007/978-981-16-4729-1
ISBN:	9789811647291$q(electronic bk.)

Big data analytics in cognitive social media and literary textstheory and praxis /
Big data analytics in cognitive social media and literary textstheory and praxis /[electronic resource] :edited by Sanjiv Sharma, Valiur Rahaman, G. R. Sinha. - Singapore :Springer Singapore :2021. - xxix, 300 p. :ill. (chiefly col.), digital ;24 cm.

Chapter 1. The Concept of Cognitive Social Media and Cognitive Literary Studies (Valiur Rahaman)-Chapter 2. Big Data Analytics for Market Prediction via Consumer Insight (Hemant Kumar Soni) -- Chapter 3. Deconstructive Big Data Analytics: A Literary Texts Analysis through Atlas.ti Software (Valiur Rahaman) -- Chapter 4. Study of Big Data Analytics Tool: Apache Spark (GL Prajapati) -- Chapter 5. Analyzing Women Health-related Quality of Life Using Sentiment Analysis on Social Media -- Chapter 6. Understanding Literary Diaspora for Digital Diasporas as Cognitive Social Media: BDA for Peace and Harmony (Ajay Kumar Chaubey) -- Chapter 7. Security and Privacy Challenges for Big Data on Social Media (Vineet Raj Singh Kushwah) -- Chapter 8. Social Media: The Dark Horse of Market in Consumer Decision Journey (Sakshi Agarwal)

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 & communication studies and computational/digital humanities.

ISBN: 9789811647291$q(electronic bk.)

Standard No.: 10.1007/978-981-16-4729-1doiSubjects--Topical Terms:

908867
Cognition
--Data processing.

LC Class. No.: QA76.9.B45 / B54 2021

Dewey Class. No.: 005.7

Big data analytics in cognitive social media and literary textstheory and praxis /
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505 0 $a Chapter 1. The Concept of Cognitive Social Media and Cognitive Literary Studies (Valiur Rahaman)-Chapter 2. Big Data Analytics for Market Prediction via Consumer Insight (Hemant Kumar Soni) -- Chapter 3. Deconstructive Big Data Analytics: A Literary Texts Analysis through Atlas.ti Software (Valiur Rahaman) -- Chapter 4. Study of Big Data Analytics Tool: Apache Spark (GL Prajapati) -- Chapter 5. Analyzing Women Health-related Quality of Life Using Sentiment Analysis on Social Media -- Chapter 6. Understanding Literary Diaspora for Digital Diasporas as Cognitive Social Media: BDA for Peace and Harmony (Ajay Kumar Chaubey) -- Chapter 7. Security and Privacy Challenges for Big Data on Social Media (Vineet Raj Singh Kushwah) -- Chapter 8. Social Media: The Dark Horse of Market in Consumer Decision Journey (Sakshi Agarwal)
520 $a 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 & communication studies and computational/digital humanities.
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