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The information diffusion links can be used to reconstruct potentially several information diffusion cascades (also called "diffusion trees"), where the root is a user who favorited a photo without having any followees who favorited it before.
Therefore, we consider roots of our diffusion trees all the users that comply with the following strict temporal sequence: (1) user u joins group g; (2) photo p is uploaded to g; (3) u favorites p. .
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Figure 13 Example of diffusion tree for a photo p uploaded into the photo pool of group g.
In practice, we take a seed message posted by s at time t 0 and include all of s followers in the diffusion tree hanging from s.
In this example 8 users out of 20 members are nodes of the diffusion tree, leading to coverage g, p = 0.4.
Next, for each cascade we compute how many nodes in the resulting diffusion tree belong to the same cluster of the seed ( n int ).
Namely, two nodes sharing a follower may show simultaneous activity, but their follower can only be counted in one or the other cascade (with possible consequences regarding cascade size distributions or depth in the diffusion tree).
Considering A g, p to be the set of adopters, namely the users who take part in the diffusion tree for the ( g, p ) pair, and M g the members of group g, we define: c g, p = | A g, p ∩ M g | | M g |, (12).
Figure 2 Diffusion for tree texture.
SPREAD provides four templates to analyze and visualize different aspects of phylogeographic diffusion, labeled: Discrete Tree, Discrete Bayes Factors, Continuous Tree and Time Slicer.
Future work could take into account ischemic regions computed using coronary artery tree diffusion models which may also affect the right ventricle.
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