“Researchers at the University of Chicago’s Data Science for Social Good programme have created the Legislative Influence Detector. This scours the text of US bills, searching for passages that have been cribbed from lobbyists or the legislatures of other states. To get the real story behind a bill, the software digs through 500,000 state bills, as well as thousands of pieces of text drafted by lobbyist groups that were saved into a database. An algorithm then calculates the top 100 documents most relevant to the bill in question before examining each one more closely, searching for passages the two have in common.”

“At the University of Texas at Arlington, computer scientist Chengkai Li is building a system to fact-check the statements of politicians in real time. The ClaimBuster, as he’s calling it, will study work done by human fact-checkers and, with the help of machine learning, start automating some of that process. Li envisions a final platform that can scan through the transcript of a speech or presidential debate, picking out the lines that we already know to be true or false so journalists can work on checking more complicated claims.”

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