Twitter is a great example of a company that relies on Mechanical Turk to improve real-time search. In a recent post to their engineering blog, Edwin Chen, a data scientist at Twitter, provides insight into how Mechanical Turk Workers improve their understanding of popular search queries as events happen.
In order to understand what users are searching for in real-time, Twitter developed a process to quickly identify trending search queries, send them to Workers on Mechanical Turk to be judged, and incorporate the data into their back-end models. For instance, when the search query “Big Bird” started spiking in association with a comment from Mitt Romney in a 2012 presidential debate, Twitter was able to quickly determine that users weren’t searching for tweets related to Sesame Street. Making this determination quickly enables Twitter to serve more relevant advertising, as opposed to ill-placed ads for Dora the Explorer.
Read Twitter’s post to learn more about how they were able to create a scalable model for collecting high quality human judgments on demand by building a custom pool of Mechanical Turk Workers using Qualifications.
Note: This isn’t the first time we’ve talked about Twitter on the Mechanical Turk blog—we highlighted their work back in August with their launch of Clockwork Raven, an open source web application built on Mechanical Turk.