Predicting which stories will become popular is an invaluable tool for newsrooms. Eui-Hong Han and Shuguang Wang explain how the Washington Post predicts what stories on its site will be popular with readers and share the challenges they faced in developing the tool and metrics on how they refined the tool to increase accuracy.
Table of contents
- Title: How the Washington Post uses machine learning to predict article popularity
- Release date: May 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920457190
You might also like
Storytelling with Data
Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience …
Data Science from Scratch, 2nd Edition
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, …
51+ hours of video instruction. Overview The professional programmer’s Deitel® video guide to Python development with …
Python Crash Course, 2nd Edition
This is the second edition of the best selling Python book in the world. Python Crash …