Year Zero

From the Nieman Journalism Lab Blog: “The journalism unicorn exists. I’ve seen one — even worked with one. Maybe you know the kind: a journalist who’s as nimble and dynamic as a reporter as she is with coding.” The Brown Institute is collaborating on a post-bacc program to help prepare journalists for the J-School’s Dual Degree

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The Declassification Engine in Poynter

Poynter has just posted a fantastic writeup of one of this year’s Magic Grants, the Declassification Engine. Co-funded by the Tow Center for digital Journalism, the Declassification Engine will “create a critical mass of declassified documents by aggregating all the archives that are now just scattered online” and apply machine learning techniques to “reveal patterns in official

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Robust detection of hyper-local events from geotagged social media data

Authors Xie K., Xia C., Grinberg N., Schwartz R., and Naaman M. Architecture of our local event detection system. Including data collector, time-series builder, Gaussian Process regression model, alert engine and classifier. Arrows indicate input and output flow of each module. Abstract An increasing number of location-annotated content available from social media channels like Twitter,

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Making Sense of Cities Using Social Media: Requirements for Hyper-Local Data Aggregation Tools

Authors Schwartz, R., Naaman M., Matni, Z. Examples of geo-tagged social media data visualizations mockups. Clockwise: geo-tagged topic groupings, keywords appearance graphs, volume graph and heat map Abstract As more people tweet, check-in and share pictures and videos of their daily experiences in the city, new opportunities arise to understand urban activity. When aggregated, these

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