Evolution properties of the community members for dynamic networks
- Yang, Kai Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai, China
- Guo, Qiang Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai, China
- Li, Sheng-Nan Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai, China
- Han, Jing-Ti Data Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, Shanghai, China
- Liu, Jian-Guo Data Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, Shanghai, China - Department of Physics, University of Fribourg, Switzerland
-
18.03.2017
Published in:
- Physics Letters A. - 2017, vol. 381, no. 11, p. 970–975
English
The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities they joined in for these data sets. Then we introduce a parameter φ to describe community evolution between different slices and investigate the dynamic community properties of the new community members. The empirical analyses for the Facebook, APS, Enron and Wiki data sets indicate that both the number of new members and joint communities increase, the ratio declines rapidly and then becomes stable over time, and most of the new members will join in the small size communities that is s≤10s≤10. Furthermore, the proportion of new members in existed communities decreases firstly and then becomes stable and relatively small for these data sets. Our work may be helpful for deeply understanding the evolution properties of community members for social networks.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Physique
- Language
-
- English
- Classification
- Physics
- License
- License undefined
- Identifiers
-
- RERO DOC 288730
- DOI 10.1016/j.physleta.2017.01.030
- Persistent URL
- https://folia.unifr.ch/unifr/documents/305583
Statistics
Document views: 25
File downloads:
- liu_epc.pdf: 42