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NetTide

Ref:
@inproceedings{Zang2016BeyondST,
title={Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications},
author={Chengxi Zang and Peng Cui and Christos Faloutsos},
booktitle={KDD},
year={2016}
}

More details in the upcoming journal version.
More info on the Social Dynamics and beyond: http://media.cs.tsinghua.edu.cn/~multimedia/cuipeng/

Author: Chengxi Zang
Date: 2017-05-01

C++:

Goal: Generate realistic growth dynamics, both for node and link, of social networks.

The growth dynamics of node and link are captured by NETTIDE equations:

Node adoption:

n-dot = beta / t^theta * n * (N - n) 

Link build between infected-infected and infected-newly infected:

e-dot = beta_prime / t^theta * n * ( alpha * (n-1)^gamma - e/n ) + 2*n-dot 

Assumption:

beta and beta_prime : growth rate of nodes and links; 
1/t^theta : fizzling effect 
the alpha and gamma describe the average number of friends in the ego network.

Two generators:

NetTide-Process: captures the micro-level stochastic interactions within a network.
NetTide-Survival: captures the growth dynamics from hazard rates (hazard process).

Input:

Input network, reads the edge file Data format: blank-separated pairs , e.g 0 1 represents 0->1 Network: e.g.,

	1.Complete network, ra ndom network 
	2.Kronecker network 
	3.Or any other network 

Nodes have been numbered 0-$n-1$ Parameters: beta, theta, beta_prime, alpha, gamma, N

Output:

n(t) over time
e(t) over time. For NetTide-Process, detailed evovling process of nodes and links are recorded.

Matlab:

Goal: Fit the growth dynamics by NetTide model, plot, and regenerate them.