Feature Story: Analyzing Social Streams

The stream of digital information is growing inexorably. One of the major challenges of scientists, curators and news agencies is to find the relevant patterns in this stream of information. A first approch to identify relevant patterns in big data could be the visualization of the data. SocialFlow, a social media optimization platform, analyzed some weeks ago, Osama bin Laden’s death. In their study they looked at 14.8 millions tweets and bitly links with the goal of reaching an understanding on how timing, along with other core dynamics can amplify the reach of a single tweet to a massive scale. Their visualizations give a first impressions of the flow of data and involved persons. An approch like that can help finding the needle in the haystack. 

CASCADE, a New York Times Reasearch and Development Lab project, focus on similar goals.  According the project description, Cascade allows for precise analysis of the structures which underly sharing activity on the web. This first-of-its-kind tool links browsing behavior on a site to sharing activity to construct a detailed picture of how information propagates through the social media space.

Visualizing big data is becoming an important approach to understand information. There are still a lot of challenges to cope with but the first results are promising.

  • Twitter
  • Facebook
  • LinkedIn
  • Netvibes
  • StumbleUpon
  • Digg
  • NewsVine
  • Google Bookmarks

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Seventh Framework Programme


Dr. Wim Peters

Adress: Department of Computer Science Regent Court 211 Portobello Sheffield S1 4DP UK
Phone: +44 114 222 1902
Email: W.Peters@dcs.shef.ac.uk
Website: The University of Sheffield