In the branching process model, a very simplified network structure is assumed. For real-world networks, a more general model should be applied. In order to allow for arbitrary graphs with cycles, we have to distinguish three states for each node:

• Susceptible nodes have not been infected yet and are therefore available for infection. They do not infect other nodes.
• Infectious nodes have been infected and infect other nodes with a certain probability.
• Removed (recovered) nodes have gone through an infectious period and cannot take part in further infection (neither actively nor passively).

Using these three states S, I, and R, and the length…

When examining the spread of diseases inside a population, not only the contagiousness of the disease, but also the structure of the network connecting the population determine the progress of the infection, as Easley and Kleinberg describe in . Because messages in a social network spread in a very similar way as diseases or ideas, we try to model the discovery phase of a tweetflow invocation using infection modelling.

In tweetflow terms, the contagiousness of a disease for a node corresponds to the payoff (reward – effort) of the tweetflow and the skill of the node. The length of the…