Big Data Deep Analytics for Geosocial Networks

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Author(s): Muhammad Mazhar Ullah Rathore (Kyungpook National University, South Korea), Awais Ahmad (Yeungnam University, South Korea)and Anand Paul (Kyungpook National University, South Korea)
Copyright: 2018
Pages: 21
Source title: Deep Learning Innovations and Their Convergence With Big Data
Source Author(s)/Editor(s): S. Karthik (SNS College of Technology, Anna University, India), Anand Paul (Kyungpook National University, South Korea)and N. Karthikeyan (Mizan-Tepi University, Ethiopia)
DOI: 10.4018/978-1-5225-3015-2.ch007

Keywords: Artificial Intelligence / Computer Science & IT / Data Mining and Databases / Information Science Reference

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Abstract

Geosocial network data provides the full information on current trends in human, their behaviors, their living style, the incidents and events, the disasters, current medical infection, and much more with respect to locations. Hence, the current geosocial media can work as a data asset for facilitating the national and the government itself by analyzing the geosocial data at real-time. However, there are millions of geosocial network users, who generates terabytes of heterogeneous data with a variety of information every day with high-speed, termed as Big Data. Analyzing such big amount of data and making real-time decisions is an inspiring task. Therefore, this book chapter discusses the exploration of geosocial networks. A system architecture is discussed and implemented in a real-time environment in order to process the abundant amount of various social network data to monitor the earth events, incidents, medical diseases, user trends and thoughts to make future real-time decisions as well as future planning.

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