Collaboration and followership: A stochastic model for activities in social networks.

ABSTRACT: In this work we investigate how future actions are influenced by the previous ones, in the specific contexts of scientific collaborations and friendships on social networks. We describe the activity of the agents, providing a model for the formation of the bipartite network of actions and their features. Therefore we only require to know the chronological order in which the actions are performed, and not the order in which the agents are observed. Moreover, the total number of possible features is not specified a priori but is allowed to increase along time, and new actions can independently show some new-entry features or exhibit some of the old ones. The choice of the old features is driven by a degree-fitness method: indeed, the probability that a new action shows one of the old feature

SUBMITTER: Becatti C 

PROVIDER: S-EPMC6821107 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature