This course explores computational journalism, an emerging field at the intersection between computation and journalism.
The main focus of this course is on the computational tools that facilitate journalism — tools that automate story discovery, generate articles, mine data, create visualizations, aggregate sources, host citizen reports, and so on. These tools can find and facilitate stories that would otherwise go unreported, lowering the opportunity cost for a resource-strapped newsroom to pursue investigative reporting. Tools can use artificial intelligence to help journalists in breaking news situations quickly release stories about document collections or datasets that would take too long to manually comprehend. In addition to reducing workload, tools can help journalists share successful story templates, for example reproducing a national investigation in local newsrooms.
As a secondary focus, this course is concerned with reporting about algorithms. Journalists equipped with computational understanding can bring accountability to the automated processes that influence our lives behind the scenes. Large tech companies like Google and Facebook exert power by ordering search results and newsfeeds, promoting political advertisements, and tracking user data — all opaque automated processes. Algorithms affect all walks of life, from credit scores, renter databases, and political profiling to serving sentencing decisions and gerrymandering districts.
This course is divided into three units: stories by algorithms, stories through algorithms, and stories about algorithms. Each unit will be divided into three phases:
This unit covers the process by which stories are written algorithmically.