A coevolving model based on preferential triadic closure for social media networks

Abstract

The dynamical origin of complex networks, i.e., the underlying principles governing network evolution, is a crucial issue in network study. In this paper, by carrying out analysis to the temporal data of Flickr and Epinions–two typical social media networks, we found that the dynamical pattern in neighborhood, especially the formation of triadic links, plays a dominant role in the evolution of networks. We thus proposed a coevolving dynamical model for such networks, in which the evolution is only driven by the local dynamics–the preferential triadic closure. Numerical experiments verified that the model can reproduce global properties which are qualitatively consistent with the empirical observations.

From sparse to dense and from assortative to disassortative in online social networks

“…It is shown that this simple reaction-diffusion-like model can reproduce statistical properties consistent with real data33. In this present paper we investigate, through modeling and simulations, the two remarkable observations that some OSNs are dense and/or disassortative.…”

Rethinking the Concept of Just Noticeable Difference in Online Marketing

“…One of the limitations is that only two artificially generated social networks were used. On the other hand the algorithm for their building was properly tested and validated in previous studies (Li et al, 2013) and further tests with different social networks generated by the same algorithm showed consistent results. And because the findings are more of qualitative nature this limitation should not undermine them.…”

“…Agents in this model represent consumers which have undirected links to others which shape their social interactions -in this case information spreading and receiving. The model is based on network topology building algorithm suggested by Li et al (2013) and Li et al (2014) which allows to generate artificial social networks with realistic properties, a given average degree (amount of social relationships) and amount of nodes (agents, i.e. consumers).…”

“…The state function is calculated using the following reaction-diffusion-like equation (Li et al, 2013):…”

Triadic Closure Pattern Analysis and Prediction in Social Networks

“…Since it is unrealistic to get global information for preferential attachment processes to establish new social ties, the triadic closure principle, whose assumption is that a node's linking dynamics only rely on its neighbors or next neighbors is relevant to social network formation. Klimek et al [17] and Li et al [23] both declared that triadic closure could be identified as one of the fundamental dynamic principles in social multiplex network formation/evolution. [6], [7], [20] also provided some triadic-closure-based network generation models.…”