For the last several months I’ve been working on a whitepaper for the CUNY Tow-Knight Center for Entrepreneurial Journalism. It’s about cultivating more technical innovation in journalism and involves systematically mapping out what’s been done (in terms of research) as well as outlining a method for people to generate new ideas in computational journalism. I’m happy to say that the paper was published by the Tow-Knight Center today. You can get Jeff Jarvis’ take on it on the Tow-Knight blog, or for more coverage you can see the Nieman Lab write-up. Or go straight for the paper itself.
Need a Job?I am seeking a research scientist to work on computational journalism projects relating to algorithmic accountability reporting, news automation & bots, and data science / journalism with me. See the post here: https://ejobs.umd.edu/postings/35785
AboutI'm an Assistant Professor at the University of Maryland, College Park College of Journalism. I study computational and data journalism with an emphasis on algorithmic accountability, narrative data visualization, and social computing in the news. I'm also a consultant specializing in research, design, and development for computational media applications. Find me on Twitter: @ndiakopoulos
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