Documentation for the project “The impact of asymmetric information-flow on the power-law exponent”

A power-law distribution for the connectivities of the nodes in a complex network has been widely reported in the studies of diverse networks. Though preferential attachment (PA) has been well accepted as an explanation for the power-law distributions observed in many systems, it is unclear how the asymmetry of information-flow in the networks will influence the power-law exponent. We show that the asymmetry of information-flow in a network plays a crucial role in resulting in different power-law exponents. With this understanding, we explain the power-law distributions of a citation network, a hyperlink network, and a relationship network in real world in a unified way.

Here is the documentation for the codes used for this study.

Table of Contents

  1. Installation
  2. Preprocessing the datasets (optional)
  3. Analytical results vs. simulations
  4. Fitting the model to real-world datasets

1. Installation

Download the folder “projects/PA-asymmetry” (temporarily available by email request), go into the folder and run the following bash commands:

pip install -r requirements.txt

python download_datasets.py

2. Preprocessing the datasets (optional)

This step is optional after downloading the datasets that have already included the preprocessed ones.

Here are the codes for preprocessing the datasets (in case needed):

  • “children_gen.py” is for generating the children;
  • “parents_gen.py” is for generating the parents;
  • “children_sizes.py” is for generating the sizes of the children;
  • “parents_sizes.py” is for generating the sizes of the parents.

3. Analytical results vs. simulations

Running “draw-pdf-sim.py” you will get the following figure in the folder “PA-asymmetry/figs/”:

Figure2

4. Fitting the model to real-world datasets

Running “draw-pdf-sim.py” you will get the following figure in the folder “PA-asymmetry/figs/”:

Figure3

Feedback: comment below or sent me an email.

Publication: (preparing)

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