The 2016 Presidential Elections will standout in history as one of the most highly contested, racially-charged, controversial and often bizarre races. Keeping up with a fast-paced, competitive news cycle as part of the data team for Univsion's Fusion Media Group was no small challenge. 

More than 22 candidates entered the fray. As the race narrowed, Bernie Sanders and Hillary Clinton took the lead on the Democratic side; Donald Trump rose through the Republican ranks. Media followed the race with an unprecedented intensity, relying more than ever on social media to drive traffic.  

Here are some highlights of the data-driven stories we developed. 

Create timely, news-worthy, data-driven stories focused on the 2016 Presidential Elections

Fusion Media Group had a 3-person data team, including Daniel McLauglin, Ross Goodwin and Sam Levine, and was looking to add a team member with journalism experience who could help define, package and write data stories. As the team evolved, Kate Stohr's role shifted to include more Python coding, data mining, partnership development and overall project management. 

Responsible for:

  • Data mining

  • Data analysis

  • Data visualization

  • Bot development

  • Data scraping/API

  • Story production

  • Deadline management

Python, AWS, MongoDB





Start Date: January 2016
End Date:  November 2016
Status: Complete

Fusion Media Group (Univision) 

Data team: Kate Stohr, Daniel McLaughlin, Ross Goodwin, Sam Levine

Editors: Erin McClam, Kashmir Hill, Alexis Madrigal

Interactive: Rachel Schallom
Innovation: Sam Ford

Data Researchers: 
Taniesha Broadfoot (99 Antennas) 
Rachel Connolly Kwock (99 Antennas) 
Grace Walker (99 Antennas) 
Monica White (99 Antennas)