Immediately implementable code, with extensive and varied illustrations of graph variants and layouts.

Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation.

Dedicated chapter on graph visualization methods.

Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment.

Various downloadable data sets for use both in class and individual learning projects.

Final chapter dedicated to individual or group project examples.

About the Author

Keith McNulty, PhD is a leading practitioner of applied mathematics, statistics, psychometrics and people analytics. He is currently Global Director of Talent Science and Analytics at McKinsey & Company.

Reviews

"It is exciting and inspiring to see the way McNulty explains network methods, as he unpacks the distinct elements and analytic steps to make them transparent. This makes it easier for readers to see how these elements fit together and apply to organizational challenges, sparking new ideas for innovative solutions. By demystifying this topic, McNulty empowers people to find their own solutions and engage in more productive conversations, regardless of who is writing the actual code or running the analyses. This book can help to democratize network analysis and improve the level of data fluency in organizations more generally."

- From the foreword by Professor Jeff Polzer, Harvard Business School

Book Information
ISBN 9781032204970
Author Keith McNulty
Format Paperback
Page Count 268
Imprint Chapman & Hall/CRC
Publisher Taylor & Francis Ltd
Weight(grams) 444g