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

Li M, Zou H, Guan S, Gong X, Li K, Di Z, Lai CH - Sci Rep (2013)

Bottom Line: 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.Numerical experiments verified that the model can reproduce global properties which are qualitatively consistent with the empirical observations.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, East China Normal University, Shanghai. 200241, P. R. China.

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.

Show MeSH
Comparing the properties of the model network with that of the empirical networks.(a)–(b) Characterizing the local influence patterns among users in the model, as compared with Figs. 2(e) and 2(f). (c)–(d) Characterizing the correlations between neighboring users and items in the model and in the empirical networks, i.e.,  and . The parameters for the model are the same as in Fig. 3.
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f5: Comparing the properties of the model network with that of the empirical networks.(a)–(b) Characterizing the local influence patterns among users in the model, as compared with Figs. 2(e) and 2(f). (c)–(d) Characterizing the correlations between neighboring users and items in the model and in the empirical networks, i.e., and . The parameters for the model are the same as in Fig. 3.

Mentions: In previous empirical analysis, we have revealed that the users' behaviors correlate with each other in the neighborhood, as shown in Figs. 2(e) and 2(f). It is found that the model can reproduce similar correlation patterns for neighboring users, as shown in Figs. 5(a) and 5(b). Since Flickr and Epinions have two types of nodes, it is also important to investigate the correlation between neighboring users and items. To this end, we calculated the average nearest neighbors' degree22. Here the term “neighbors” specially refers to the relation between users and their connecting items. We defined two quantities: the average popular degree of user i's favorite items and the average favorite degree of item λ's fans as


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

Li M, Zou H, Guan S, Gong X, Li K, Di Z, Lai CH - Sci Rep (2013)

Comparing the properties of the model network with that of the empirical networks.(a)–(b) Characterizing the local influence patterns among users in the model, as compared with Figs. 2(e) and 2(f). (c)–(d) Characterizing the correlations between neighboring users and items in the model and in the empirical networks, i.e.,  and . The parameters for the model are the same as in Fig. 3.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3753589&req=5

f5: Comparing the properties of the model network with that of the empirical networks.(a)–(b) Characterizing the local influence patterns among users in the model, as compared with Figs. 2(e) and 2(f). (c)–(d) Characterizing the correlations between neighboring users and items in the model and in the empirical networks, i.e., and . The parameters for the model are the same as in Fig. 3.
Mentions: In previous empirical analysis, we have revealed that the users' behaviors correlate with each other in the neighborhood, as shown in Figs. 2(e) and 2(f). It is found that the model can reproduce similar correlation patterns for neighboring users, as shown in Figs. 5(a) and 5(b). Since Flickr and Epinions have two types of nodes, it is also important to investigate the correlation between neighboring users and items. To this end, we calculated the average nearest neighbors' degree22. Here the term “neighbors” specially refers to the relation between users and their connecting items. We defined two quantities: the average popular degree of user i's favorite items and the average favorite degree of item λ's fans as

Bottom Line: 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.Numerical experiments verified that the model can reproduce global properties which are qualitatively consistent with the empirical observations.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, East China Normal University, Shanghai. 200241, P. R. China.

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.

Show MeSH