Inferring networks of diffusion and influence

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by Gomez Rodriguez, M.; Leskovec, J. & Krause, A.

In order to study network diffusion, we need to

  1. identify the contagion (idea, information, virus, phrase),
  2. track the contagion,
  3. infer the diffusion network based on the observed node/time of infection-pattern.
This article discusses an algorithm for inferring diffusion networks based on this information and presents experiments based on

  1. simulated network structures, and
  2. a dataset containing more than 172 million news articles from 1 million online sources mirrored between September 2008 and August 2009.
The authors use MemeTracker to identify more than 343 million textual phrases (=contagion) to track over time.