Finding and assessing social media information sources in the context of journalism

  • Authors:
  • Nicholas Diakopoulos;Munmun De Choudhury;Mor Naaman

  • Affiliations:
  • Rutgers University, New Brunsick, New Jersey, United States;Rutgers University & Microsoft Research, New Brunsick, New Jersey, United States;Rutgers University, New Brunswick, New Jersey, United States

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2012

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Abstract

Social media is already a fixture for reporting for many journalists, especially around breaking news events where non-professionals may already be on the scene to share an eyewitness report, photo, or video of the event. At the same time, the huge amount of content posted in conjunction with such events serves as a challenge to finding interesting and trustworthy sources in the din of the stream. In this paper we develop and investigate new methods for filtering and assessing the verity of sources found through social media by journalists. We take a human centered design approach to developing a system, SRSR ("Seriously Rapid Source Review"), informed by journalistic practices and knowledge of information production in events. We then used the system, together with a realistic reporting scenario, to evaluate the filtering and visual cue features that we developed. Our evaluation offers insights into social media information sourcing practices and challenges, and highlights the role technology can play in the solution.