Patterson’s task is becoming increasingly common in newsrooms. Journalists at ProPublica, Forbes, The New York Times, Oregon Public Broadcasting, Yahoo!, and others are using algorithms to help them tell stories about business and sports as well as education, inequality, public safety, and more. For most organizations, automating parts of reporting and publishing efforts is a way to both reduce reporters’ workloads and to take advantage of new data resources. In the process, automation is raising new questions about what it means to encode news judgment in algorithms, how to customize stories to target specific audiences without making ethical missteps, and how to communicate these new efforts to audiences.
Automation is also opening up new opportunities for journalists to do what they do best: tell stories that matter. With new tools for discovering and understanding massive amounts of information, journalists and publishers alike are finding new ways to identify and report important, very human tales embedded in big data.
Can automating reporting lead the way back to fact-based news?
(Score: 2, Redundant) by M. Baranczak on Thursday September 03 2015, @07:12PM
(Score: 1) by Ethanol-fueled on Thursday September 03 2015, @09:28PM
Yup, FoxNews does that as well. To elaborate, the "filler" is getting a few people to discuss the news and react emotionally and hysterically with opinion (specifically the agenda of that particular news network) rather than fact. Think Reddit, except that everybody has Downs Syndrome and is speaking live on TV.
Sometimes there will be a guest with a dissenting voice who is ganged up on by the other 2-3 people and is often made to look either wimpy or a unlikeable caricature even more outrageous than the others.
My main gripe is what American mainstream news isn't reporting about. The Snowden leaks, for example -- the mainstream stopped reporting them when it was revealed that all NSA data is sent directly to Israel unredacted. Any criticism of Israel is conspicuously absent from both the Right and Left-sided networks.