analysis of rumor spread in complex social networks using multiple parameters - trust mechanism, hibernation and counterattack.
Link - http://snap.stanford.edu/data/facebook_combined.txt.gz
This dataset consists of 'circles' (or 'friends lists') from Facebook. Facebook data was collected from survey participants using this Facebook app.
Dataset statistics | |
---|---|
Nodes | 4039 |
Edges | 88234 |
Average clustering coefficient | 0.6055 |
Number of triangles | 1612010 |
Fraction of closed triangles | 0.2647 |
Diameter (longest shortest path) | 8 |
90-percentile effective diameter | 4.7 |
- implementation and analysis of SIR model with Trust Mechanism [2]- Trust_in_SIR.ipynb
- implementation and analysis of SIHR model [3] - SIHR.ipynb
- implementation and analysis of SICR model [4] - SICR.ipynb
- implementation of SICHR model with Trust Mechanism - SIHCR_Trust.ipynb
- analysis of models on Facebook Social Circles network [5] - facebook_network_analysis.ipynb
- block diagram of SIHCR model with Trust Mechanism - SIHCR_trust_block_dia.png
[1] M. Nekovee, Y. Moreno, G. Bianconi, and M. Marsili. Theory of rumour spreading in complex social networks. Physica A: Statistical Mechanics and its Applications,374(1):457–470, 2007
[2] Ya-Qi Wang, Xiao-Yuan Yang, Yi-Liang Han, and Xu-An Wang. Rumor spreading model with trust mechanism in complex social networks. Communications in Theoretical Physics, 59(4):510–516, apr 2013.
[3] Laijun Zhao, Jiajia Wang, Yucheng Chen, Qin Wang, Jingjing Cheng, and Hongxin Cui. SIHR rumor spreading model in social networks. Physica A: Statistical Mechanics and its Applications, 391(7):2444–2453, 2012.
[4] Yongli Zan, Jianliang Wu, Ping Li, and Qinglin Yu. SICR rumor spreading modeling complex networks: Counterattack and self-resistance. Physica A: Statistical Mechanics and its Applications, 405:159–170, 2014.
[5] Jure Leskovec, et al. "SNAP Datasets: Stanford Large Network Dataset Collection." http://snap.stanford.edu/data. (2014).