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Fundamentals of big data network analysis for research and industry / Hyunjoung Lee and Il Sohn

By: Contributor(s): Material type: TextTextPublication details: United Kingdom : John Wiley & Son, Inc., c2016Description: xviii, 196 pages : illustrations ; 24 cmISBN:
  • 9781119015581
Subject(s): LOC classification:
  • QA 76.9 .L44 2016
Contents:
1. Why big data? -- 2. Basic programs for analyzing networks -- 3. Understanding network analysis -- 4. Research methods using SNA -- 5. Position and structure -- 6. Connectivity and role -- 7. Data structure in NetMiner -- 8. Network analysis using NetMiner.
Summary: 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 Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis.
Item type: Books
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Holdings
Item type Current library Home library Collection Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Graduate Studies General Circulation Gen. Ed - CEAS GC QA 76.9 .L44 2016 (Browse shelf(Opens below)) c.1 Available NULIB000013850

Includes bibliographical references and index.

1. Why big data? -- 2. Basic programs for analyzing networks -- 3. Understanding network analysis -- 4. Research methods using SNA -- 5. Position and structure -- 6. Connectivity and role -- 7. Data structure in NetMiner -- 8. Network analysis using NetMiner.

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 Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis.

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