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Saturday, October 24 • 10:00 - 11:00
How algorithms find and spread news [E]

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Coaching Computers to Detect and Verify News from Social Media

The use of social media as a source of news is entering a new phase as computer algorithms are developed and deployed to detect, rank, and verify news. The efficacy and ethics of such technology is the subject of this talk, which examines once such tool, Social Sensor. Social Sensor is being used successfully to identify trending news stories, allow journalists to search within social media, and help verify social media contributors and content. However such software also raises questions about who has influence as social media is algorithmically-filtered for the benefit of journalists and others.

Prof. Dr. Neil Thurman (Institut für Kommunikationswissenschaft und Medienforschung, LMU München)

The news will find you - the question is how

News organisations have to face a constant change in how users are consuming their stories. Be it print, desktop, tablet, smartwatch, smart-tv or other devices - we'll have to understand in which situation at whicht time which content ist best for our customers. The Internet of things will help us to get a better understanding on the situation. We'll need to learn that the next learning curve for us as news producer will be how we can use sensors in a privacy-acceptable way to serve news stories in the future.

Marco Maas (OpenDataCity)


Referenten
avatar for Marco Maas

Marco Maas

CEO, Datenfreunde GmbH
Storytelling, Internet of Things, Sensors, Data, Data Journalism, Innovation, Startup-Stuff, Company Building
avatar for Neil Thurman

Neil Thurman

Professor, LMU München
Neil Thurman is a Professor of Communication at LMU Munich and a Volkswagen Foundation Freigeist Fellow. He was the first faculty member in electronic publishing at City, University of London and has directed Master’s programmes in Electronic Publishing and Journalism and Globalization... Read More →


Saturday October 24, 2015 10:00 - 11:00 CEST
Saal Erich-Brost-Haus, TU Dortmund

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