We provide the data and implementations that were used to evaluate the practical applications of the DRGG model. Our example used is from a word ascociation study. We also found other data sets such as http://vlado.fmf.uni-lj.si/pub/networks/data/dic/fa/FreeAssoc.htm.

Download PairsP.net from http://vlado.fmf.uni-lj.si/pub/networks/data/dic/fa/FreeAssoc.htm and add it to the cloned repo. One may start by running theoretical_degree_distribution.py to reproduce some of the graphs given in the paper.

• drgg.py a class that allows for the production of graphs following the DRGG model.
• real_world_data_metrics.py computes the different metrics (e.g. degree distribution) for data from a given data set.
• drgg_model_metrics.py computes the different metrics (e.g. degree distribution) for the DRGG simulation of a given data set.
• theoretical_degree_distribution.py the implementation of the expected behavior of DRGG that uses the theoretical results of the different properties (e.g. degree distribution) of the graph produced.
• utils.py some helper methods