Journalists, while structurally and economically under threat, are bringing computer science into their newsrooms. Their tools and techniques benefit from computer science in areas such as databases, graph analysis and machine learning and allow journalists to tackle new kinds of stories.
This lecture will be about how journalists use computer science to find the story needles in their data haystacks. CS knowledge comes in handy when scraping government websites, searching giant troves of documents and analysing social graphs. Recently popularised techniques like machine learning and other techniques can be used to explore and uncover hidden truths in datasets. New research areas such as algorithmic accountability (e. g. how can you find the cheating algorithm in the VW cars) become more important and lead to stories that require a journalistic mind to discover them but need reverse engineering skills to fully understand. I will give a roundup of how stories are told with the help of computers in newsrooms around the world. As a software engineer by trade working in an investigative newsroom I’m also applying the stuff I learn to help my reporter colleagues find and tell new kinds of stories.
Speakers: Stefan Wehrmeyer