Web and Network Data Science Modeling Techniques in Predictive Analytics

Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics.

Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications.

Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

THOMAS W. MILLER (Evanston, IL), faculty director of Northwestern University’s Predictive Analytics program, has designed and taught courses in predictive analytics, predictive modeling, marketing analytics, and advanced modeling. Also owner of Research Publishers LLC, he has worked with predictive models for 30+ years, and consults on retail site selection, product positioning, segmentation, and pricing. He holds a Ph.D. in psychology (psychometrics); and M.S. degrees in statistics, business, and economics. His books include Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R (Revised Edition); Data and Text Mining: A Business Applications Approach; and Research and Information Services: An Integrated Approach for Business. He previously directed the A.C. Nielsen Center for Marketing Research in the School of Business, U. of Wisconsin-Madison.

What Is Network Data Science?

Delivering a Message

Designing an Interface

Getting Recognized

Searching the Web

Watching Competitors

Understanding Network Structure 

Observing Communities

Measuring Sentiment 

Modeling Network Behavior

Modeling Economic Behavior

What's Next?

Master web and network modeling for predictive analysis: both theory and real-world problem solving

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