Democratic Presidential Debate Analysis Using Wolfram Language

Published February 6, 2020

When 20 presidential candidates duke it out on the debate stage, who wins? Americans have been watching a crowded and contentious primary season for the 2020 Democratic nomination for president. After the debates, everyone’s talking about who got the most talk time or attention, which exchanges were most exciting or some other measure of who “won” the night—and who might ultimately clinch a victory at the caucuses. So I decided I’d do a little exploration of the debates using the entity framework, text analytics and graph capabilities of the Wolfram Language and see if I could come up with my own measure of a “win” for a debate, based on which candidate was most central to the conversation.

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