
Web and Network Data Science
Description
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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.
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Miller is co-founder and director of product development at ToutBay, a publisher and distributor of data science applications. He has consulted widely in the areas of retail site selection, product positioning, segmentation, and pricing in competitive markets, and has worked with predictive models for over 30 years. Miller's books include Modeling Techniques in Predictive Analytics (Revised and Expanded Edition), Modeling Techniques in Predictive Analytics with Python and R, Data and Text Mining: A Business Applications Approach, Research and Information Services: An Integrated Approach for Business, and a book about predictive modeling in sports, Without a Tout: How to Pick a Winning Team.
Before entering academia, Miller spent nearly 15 years in business IT in the computer and transportation industries. He also directed the A. C. Nielsen Center for Marketing Research and taught market research and business strategy at the University of Wisconsin-Madison.
He holds a Ph.D. in psychology (psychometrics) and a master's degree in statistics from the University of Minnesota, and an MBA and master's degree in economics from the University of Oregon.
Content
1 Being Technically Inclined 1
2 Delivering a Message Online 13
3 Crawling and Scraping the Web 25
4 Testing Links, Look, and Feel 43
5 Watching Competitors 55
6 Visualizing Networks 69
7 Understanding Communities 95
8 Measuring Sentiment 119
9 Discovering Common Themes 171
10 Making Recommendations 201
11 Playing Network Games 223
12 What's Next for the Web? 233
A Data Science Methods 237
A.1 Databases and Data Preparation 240
A.2 Classical and Bayesian Statistics 242
A.3 Regression and Classification 245
A.4 Machine Learning 250
A.5 Data Visualization 252
A.6 Text Analytics 253
B Primary Research Online 261
C Case Studies 281
C.1 Email or Spam? 281
C.2 ToutBay Begins 284
C.3 Keyword Games: Dodgers and Angels 288
C.4 Enron Email Corpus and Network 291
C.5 Wikipedia Votes 292
C.6 Quake Talk 294
C.7 POTUS Speeches 295
C.8 Anonymous Microsoft Web Data 296
D Code and Utilities 297
E Glossary 313
Bibliography 321
Index 351
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- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (not Kindle).
The file format ePUB works well for novels and non-fiction books – i.e., „flowing” text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
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