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

By:

Hyunjoung Lee [author]

Contributor(s):

Sohn, Il [co-author]

Material type: Text

TextPublication details: United Kingdom : John Wiley & Son, Inc., c2016Description: xviii, 196 pages : illustrations ; 24 cmISBN:

9781119015581

Subject(s):

DATA MINING

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	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

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Previous	GC QA 76.9 .D34 2015 c.1 Data science and big data analytics: discovering, analyzing, visualizing and presenting data.	GC QA 76.9 .D34 2015 c.2 Data science and big data analytics: discovering, analyzing, visualizing and presenting data.	GC QA 76.9 .D43 2014 The Microguide to process and decision modeling : build more efficient, agile and simple solutions with process and decision modeling /	GC QA 76.9 .L44 2016 Fundamentals of big data network analysis for research and industry /	GC QA 76.27 .A38 2014 Advances in research methods for information systems research: data mining, data envelopment analysis, value focused thinking /	GC QA 76.76 .T43 2015 Quality assurance : software quality assurance made easy!.	GC QA 76.76.O63 .A53 2014 c.3 Operating systems : principles and practice /	Next

Includes bibliographical references and index.

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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