May 26, 2018 · We show that simple regression models based on graphlet frequency distribution can explain over 95% of the variance in virality on networks.

We propose using the graphlet frequency distribution in combination with assortativity to explain variations in the evolution of viral processes across networks ...

Predicting the evolution of viral processes on networks is an important problem with applications arising in biology, the social sciences, and the study of ...

This paper proposes using the graphlet frequency distribution in combination with assortativity to explain variations in the evolution of viral processes ...

May 26, 2018 · In this paper, we will be making several different measurements reflecting the topology of networks—from degree distribution to assortativity to ...

Oct 22, 2024 · We propose using the graphlet frequency distribution in combination with assortativity to explain variations in the evolution of viral processes ...

The Role of Graphlets in Viral Processes on Networks ; Journal: Journal of Nonlinear Science, 2018, № 5, p. 2309-2324 ; Publisher: Springer Science and Business ...

The role of graphlets in viral processes on networks. This is the official repository for #The-role-of-graphlets-in-viral-processes-on-networks.

By using local graphlet counts to predict event spread, our methods allow users to predict overall virality given only limited scope of the graph. In this paper ...

We propose using the graphlet frequency distribution in combination with assortativity to explain variations in the evolution of viral processes across networks ...