Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination

Software

This software is free under the terms of the GNU General Public License. It is a modified version of the code originally written by Jens Pfau, extended to include bounded confidence, support for external initial conditions data and other methods of generating initial conditions, and parallelization using MPI (with mpi4py). It also requires the Python libraries NumPy (part of the SciPy package) and igraph, and uses code written in R to compute cophenetic correlation coefficients.

The Python code was run with NumPy version 1.7.1, SciPy version 0.12.0, igraph version 0.6 and mpi4py version 1.3.1 under Python version 2.7.5 on a cluster running CentOS 5 (Linux 2.6.32-358.18.1.el6.x86_64) with Open MPI version 1.6.5. The C++ code was compiled with gcc version 4.4.7. R version 2.15.3 was used for running R scripts.

Figures and data

Figures, data, and scripts for generating the figures: figures_data.tar.gz (note, this file is very large; it is 1.1 GB compressed to download, and uncompresses to approximately 7 GB of data).

Note that the Eurobarometer and GSS data is not included due to restrictions on redistribution. However the scripts for processing the data are included, and the original data can be obtained from the locations cited in the paper.

The scripts are mostly written in R and use the following R libraries, which can be installed from the CRAN repository with the R install.packages() command: RColorBrewer, clue, doBy, ggplot2, gplots, grid, gridExtra, Hmisc, igraph, lattice, laticeExtra, methods, plyr, reshape, scales. Note that it may not be necessary to install all these libraries explicitly; some of them are dependencies of the others. The two major libraries used are ggplot2 (version 0.9.3.1) for generating plots and igraph (version 0.6.5-2) for network analysis.

Reference

If you use our software, data, or results in your research, please cite:

Stivala, A., Robins, G., Kashima, Y., and Kirley, M. (2014). Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination. Scientific Reports 4:4870. doi:10.1038/srep04870
Pfau, J., Kirley, M., and Kashima, Y. (2013). The co-evolution of cultures, social network communities, and agent locations in an extension of Axelrod's model of cultural dissemination. Physica A: Statistical Mechanics and its Applications. 392(2):381-391. doi:10.1016/j.physa.2012.09.004

Contact

Alex Stivala

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