This paper introduces an integrated temporal-causal model for dynamics in social networks addressing the contagion principle by which states are affected mutually, and both the homophily principle and the more-becomes-more principle by which connections are adapted over time. The integrated model has been evaluated in three different manners: by simulation experiments, by verification based on mathematical analysis, and by validation against an empirical data set.
|Name||Frontiers in Artificial Intelligence and Applications|
|Conference||22nd European Conference on Artificial Intelligence, ECAI 2016|
|Period||29/08/16 → 2/09/16|