Fundamentals of Big Data Network Analysis for Research and Industry
Hyunjoung Lee, Institute of Green Technology, Yonsei University, Republic of Korea
Il Sohn, Material Science and Engineering, Yonsei University, Republic of Korea
Presents the methodology of big data analysis using examples from research and industry
There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important. Contrary to popular belief, not all information is useful; big data network analysis assumes that data is not only large, but also meaningful, and this book focuses on the fundamental techniques required to extract essential information from vast datasets.
Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail.
Fundamentals of Big Data Network Analysisfor Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis.
Fundamentals of Big Data Network Analysisfor Research and Industry will prove a valuable resource for analysts, research engineers, industrial engineers, marketing professionals, and any individuals dealing with accumulated large data whose interest is to analyze and identify potential relationships among data sets.