Data Strategy

August 30, 2007

Analyzing microblogging

Filed under: Datamining, People and Data, Visualization — chucklam @ 2:40 pm

Akshay Java and colleagues at University of Maryland and NEC Laboratories presented a paper at KDD called Why We Twitter: Understanding Microblogging Usage and Communities. In the paper they analyzed the social graph of Twitter and all the public postings for two months from April 1 to May 30 of this year, so the data is very recent. The conclusions are pretty much in line with what we have come to expect from social networks (power law distribution, community clusters, etc.). In the discussion section, they classify Twitter usage into four categories:

  1. Daily chatter (dominant category)
  2. Conversations (1/8 of all posts which are started with the @ symbol follow by a username)
  3. Sharing information/URLs (13% of all posts)
  4. Reporting news (often by automated agents)

The interesting part to me was really how they collected the data. Apparently the whole Twitter network can be gotten from its API. It’s usually pretty difficult for researchers to get access to large-scale social graphs, so it’s nice to know that the Twitter social graph is easy to get. The network is smaller than I had expected though. Its total user base (at the end of May) is a little less then 88,000. The amount of attention Twitter gets seems to be much bigger than its number of users. In addition, the authors of the paper stated that “After an initial period of interest around March 2007, the rate at which new users are joining Twitter has slowed.”

1 Comment »

  1. really interesting

    Comment by acidtrash — August 30, 2007 @ 3:10 pm

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