Limits...
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

Related in: MedlinePlus

Schematic plot of the social media networks, where the items could be photos (as in Flickr), reviews (as in Epinions), videos (as in YouTube), etc.In principle, the social links (solid lines with arrowheads) are directional, while the cross links (dashed lines) are not. For these two types of links, we can define four types of degrees (see Methods for the details). For example, U4 in the network has indegree (kin = 2), outdegree (kout = 4), and favorite degree (kf = 2); I4 has popular degree (kp = 3). If the directions of social links are ignored, as we will do in the model, the links among users define the social degree (which is not the direct summation of indegree and outdegree because there is overlap between them for a user). In this case, for example, U4 has social degree (ks = 5) and favorite degree (kf = 2).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3753589&req=5

f1: Schematic plot of the social media networks, where the items could be photos (as in Flickr), reviews (as in Epinions), videos (as in YouTube), etc.In principle, the social links (solid lines with arrowheads) are directional, while the cross links (dashed lines) are not. For these two types of links, we can define four types of degrees (see Methods for the details). For example, U4 in the network has indegree (kin = 2), outdegree (kout = 4), and favorite degree (kf = 2); I4 has popular degree (kp = 3). If the directions of social links are ignored, as we will do in the model, the links among users define the social degree (which is not the direct summation of indegree and outdegree because there is overlap between them for a user). In this case, for example, U4 has social degree (ks = 5) and favorite degree (kf = 2).

Mentions: As shown in Fig. 1, Flickr and Epinions are typical dual-component networks which actually represent a broad class of social media networks consisting of users and items such as photos, videos, documents, music, blogs and so on (see Methods for data description and notations). Due to multiplex nodes and multi-relations, social media networks are more complicated than the usual networks involving only one type of node and one type of link. They are also different from the bipartite networks that are special dual-component networks studied previously25262728. In the following, we report the main findings of our empirical analysis to the Flickr and Epinions networks. Our particular attention is paid to the evolution patterns in these two networks.


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)

Schematic plot of the social media networks, where the items could be photos (as in Flickr), reviews (as in Epinions), videos (as in YouTube), etc.In principle, the social links (solid lines with arrowheads) are directional, while the cross links (dashed lines) are not. For these two types of links, we can define four types of degrees (see Methods for the details). For example, U4 in the network has indegree (kin = 2), outdegree (kout = 4), and favorite degree (kf = 2); I4 has popular degree (kp = 3). If the directions of social links are ignored, as we will do in the model, the links among users define the social degree (which is not the direct summation of indegree and outdegree because there is overlap between them for a user). In this case, for example, U4 has social degree (ks = 5) and favorite degree (kf = 2).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f1: Schematic plot of the social media networks, where the items could be photos (as in Flickr), reviews (as in Epinions), videos (as in YouTube), etc.In principle, the social links (solid lines with arrowheads) are directional, while the cross links (dashed lines) are not. For these two types of links, we can define four types of degrees (see Methods for the details). For example, U4 in the network has indegree (kin = 2), outdegree (kout = 4), and favorite degree (kf = 2); I4 has popular degree (kp = 3). If the directions of social links are ignored, as we will do in the model, the links among users define the social degree (which is not the direct summation of indegree and outdegree because there is overlap between them for a user). In this case, for example, U4 has social degree (ks = 5) and favorite degree (kf = 2).
Mentions: As shown in Fig. 1, Flickr and Epinions are typical dual-component networks which actually represent a broad class of social media networks consisting of users and items such as photos, videos, documents, music, blogs and so on (see Methods for data description and notations). Due to multiplex nodes and multi-relations, social media networks are more complicated than the usual networks involving only one type of node and one type of link. They are also different from the bipartite networks that are special dual-component networks studied previously25262728. In the following, we report the main findings of our empirical analysis to the Flickr and Epinions networks. Our particular attention is paid to the evolution patterns in these two networks.

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
Related in: MedlinePlus