In November, we’ll discuss how machine learning and natural language processing can be used in journalism.
This time we meet at c-base (https://en.wikipedia.org/wiki/C-base), which is not only one of the oldest hackerspaces in the world, but also built in the remnants of an actual crashed alien space station – but that is a different story (https://www.c-base.org/).
Elena Erdmann (https://twitter.com/elena_erdmann) is a PhD student in machine learning between TU Darmstadt and Zeit Online. In her PhD, she explores how machine learning and natural language processing can be used in the newsroom. As a member of Journocode (http://journocode.com/), she is excited about all data journalism and enjoys to pass on her knowledge and enthusiasm about it. At Hacks Hackers she will give a short introduction to Machine Learning.
Natalie Widmann (https://twitter.com/Tilana145) has a background in cognitive science and artificial intelligence. At HURIDOCS (https://huridocs.org/) she uses machine learning and natural language processing to extract information and discover patterns in large collections of documents. She will showcase how these methods support the work of human rights organisations.
Haluka Maier-Borst (https://twitter.com/halukamb) is a science and data journalist who just finished his master’s in “Computational Journalism” at Cardiff University. He will explain how he used machine learning in his master-thesis and the newsroom to cover the German elections for the Financial Times. Also, he will try to convince you that machines will not run newsrooms but could actually be your partner in crime as a reporter.
Nicolas Merz is a political scientist at the WZB Berlin Social Science Center (https://www.wzb.eu/en). He works in a project that collects, digitizes and analyzes electoral programs from political parties in over 50 countries (http://manifesto-project.wzb.eu (http://manifesto-project.wzb.eu/)). He will show various examples of how to apply automatic text analysis methods to electoral programs.