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A Brand Image Analysis of WordPress and Automattic on Twitter
As a data scientist, I spend a lot of time analyzing how our users interact with WordPress.com. However, WordPress.com isn’t the only place to gain insight into how people use and talk about our services. Many WordPress.org and WordPress.com discussions take place on social media. Analyzing these discussions can help us understand what our users are…
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Bulk Log Analytics With Hive
Leveraging the distributed powers of MapReduce to perform custom log analysis or some one-time queries on the raw data is fast and easy and you don’t even have to build a complicated ETL process to do it. The data engineering team at WordPress.com recently used this approch to query tens of billions of log lines…
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Network Science at Automattic: Mapping the Communities of WP.com — Methodology
If you have read our analysis on the communities of WordPress.com and would like to know more about the methods behind it, then keep on reading! In this — slightly more technical — post, I will show how we constructed, filtered, projected, and clustered a network around WordPress.com users and blogs. Building the Network of WP.com People…
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Intro to Search: Anatomy of a search engine
Welcome to the second post in our “Intro to Search”-series! Today, we’ll dig into the building blocks of search engines to give you an idea of just how we identify what posts to show readers using WordPress.com’s search tool. A (web) search engine connects users with relevant documents. This process generally has five main stages:…
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Network Science at Automattic: Mapping the Communities of WP.com
WordPress.com is home to hundreds of millions of sites, a place to produce and discover content. Logging in, you’re automatically taken to the Reader, where you’ll find a stream of posts from sites you follow or that we’ve recommended for you. You can like, reblog, or comment on these posts. If you’re inspired, you can choose to publish a…
Data for Breakfast 