During 2017, I was a project lead for a subsection of Data For Democracy, a group of data scientists and technically talented activists interested in making the world a better place. We were contacted by the NILC (National Immigration Law Center) after the January 2017 Muslim Ban was put into place. The NILC was in the process of suing the Trump administration, accusing them of using race or religion in their determination for what countries to ban immigration from.
The NILC was looking to compile and analyze public statements which would prove discriminatory intent to the Muslim Ban. The scope was broad and included Trump and known associates - a perfect opportunity to flex D4D’s web scraping muscles. We created visulizations using natural language processing and web scraping functions for the NILC law team.
On Wednesday, March 15th 2017, the NILC used our research to argue on behalf of the state of Maryland. After a day of deliberation, the federal judge awarded us a stay against the immigration ban. Over time, the another, albeit much weaker, version of the immigration ban ended up being approved by the courts.