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  • 标题:Prediction of Big Data Analytics (BDA) on Social Media: Empirical Study
  • 本地全文:下载
  • 作者:Ahed J Alkhatib ; Shadi Mohammad Alkhatib ; Hani Bani Salameh
  • 期刊名称:Dialogo
  • 印刷版ISSN:2392-9928
  • 电子版ISSN:2393-1744
  • 出版年度:2020
  • 卷号:7
  • 期号:1
  • 页码:225-240
  • DOI:10.18638/dialogo.2020.7.1.19
  • 语种:English
  • 出版社:Ovidius University Press
  • 摘要: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.
  • 关键词:Big Data;social media;neural network;data clustering
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