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Prediction of big data analytics (BDA) on social media : empirical study

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Author(s)
Alkhatib, Ahed J
Alkhatib, Shadi Mohammad
Salameh, Hani Bani
Keywords
Big Data
social media
neural network
data clustering
GE Subjects
Cyberethics/Information and Communication Technology ICT

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URI
http://hdl.handle.net/20.500.12424/4009171
Online Access
http://dialogo-conf.com/archive/?vid=1&aid=2&kid=170701-19
Abstract
Currently, most studies are moving towards Big Data Analytics (BDA) because they are important in research, and this is becoming increasingly important as Internet and Web 2.0 technologies become increasingly popular and how to handle this massive data. Moreover, this proliferation of the Internet and social media has revolutionized the search process. With this Big Data of data generated by users using social media or electronic platforms, the use of these details and daily activities is integrated with tools designed for analysis. The topic of analyzing big social media will be discussed and an intensive explanation will be given to the topic of Big Data. This paper compares Big Data analysis techniques using several methods of analysis, the first technique using neural networks and the second technique using data clustering. The purpose of this study is to infer the ages that use social media and what are their interests in writing and in the end, who are the most widely used social media males or females.
Date
2020-11-30
Type
Article
DOI
10.18638/dialogo.2020.7.1.19
Copyright/License
2020 RCDST. All rights reserved.
ae974a485f413a2113503eed53cd6c53
10.18638/dialogo.2020.7.1.19
Scopus Count
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Dialogo / Research Center on the Dialogue between Science & Theology (Romania)

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