Getting started with machine learning for reporting

  • Event: 2018 CAR Conference
  • Speakers: Peter Aldhous of BuzzFeed News; Chase Davis of Star Tribune; Anthony Pesce of Los Angeles Times; Rachel Shorey of The New York Times
  • Date/Time: Thursday, Mar. 8 at 4:45pm
  • Location: Grand Ballroom I
  • Audio file: Only members can listen to conference audio

Many tasks in investigative journalism boil down to classification problems. Is my police department cooking its crime stats by assigning incident reports to the wrong categories? Of the thousands of planes in the air each day, which ones might be involved in government surveillance? How can we identify political ads on Facebook? 

Drawing on examples including the LA Times' investigation into the misclassification of violent crimes by the LAPD, BuzzFeed News' identification of spy planes operating in U.S. airspace, and ProPublica's tracking of political ads on Facebook, we'll consider practical questions like: I'm not a data scientist, I'm a reporter. What's in it for me? What type of story or reporting task can machine learning help with? When is machine learning *not* the answer? Which algorithm should I choose? How can I structure my data to give the algorithm more to work with?


Speaker Bios

  • I’m a reporter on the science desk at BuzzFeed News, based in San Francisco. My data-driven projects have included the use of machine learning to find spy planes in public flight-tracking data and text analysis of the Twitter accounts of President Donald Trump and all members of Congress. @paldhous

  • Chase Davis works on initiatives related to digital transformation and strategy at the Star Tribune, in his hometown of Minneapolis. Previously he ran the Interactive News desk at The New York Times and worked as as reporter and editor in Texas, Iowa and California. He also teaches a class in advanced data journalism at his alma mater, Mizzou. @chasedavis

  • Anthony Pesce is a data journalist and reporter on the Los Angeles Times Data Desk. He builds news applications, develops data visualizations and conducts data analysis for reporting projects. @anthonyjpesce

  • Rachel is a Senior Software Engineer and Assistant Editor for Data Projects on the Interactive News team at The New York Times. She works on a variety of software and data projects, including campaign finance and voter data. In addition, she is especially excited to chat about prime numbers.

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