Hoaxy is a tool that visualizes the spread of articles online. Articles can be found on Twitter, or in a corpus of claims and related fact checking.
I began working on Hoaxy as a consultant in fall of 2016, but we were unable to get it launchable in time for the election. Months later, we got a grant to incorporate Botometer into Hoaxy.
As part of the grant, I was assigned as the lead front-end developer. We built the original prototype using JQuery, but because there would be a great deal more functionality added on for the grant, I elected to port the front-end to Vue.js. We also used NV.D3 for the timeline and Sigma.js for the network graph visualization.
The members of the Hoaxy team have changed multiple times over the course of its development. In the beginning, it has been comprised primarily of graduate students. During my time as lead developer I was given the opportunity to train and mentor many of the incoming developers on the project. After becoming IT Director, development has been taken over by my team of software engineers.
After Twitter discontinued its free API plans, OSoMe was unable to maintain Hoaxy's search capabilities directly. It now offers a few free searches, afterwhich a user with a paid plan must input their bearer token and use their own search quota.
An older, open source version of Hoaxy's frontend code can be found on GitHub.