Replication data and code for "Prestige drives epistemic inequality in the diffusion of scientific ideas"
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epidemic Save sample epidemic simulation Oct 15, 2018
imports Move files into subdirectories when possible, and fix getplots runtim… Mar 7, 2018
publications
results
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LICENSE
README.md
_config.yml
getplots.py
plot_utils.py
prestige.py
updatebusinessresults.py
updatecompsciresults.py Save sample epidemic simulation Oct 15, 2018
updatehistoryresults.py

README.md

Epistemic Inequality

Replication data and code for "Prestige drives epistemic inequality in the diffusion of scientific ideas"

cache

Contains pickles of epidemic size and length. The script summary.py will return how many simulations were run for each transmission probability, and each particular starting node. Each cache of the SI model contains 1000 trials for each node, transmission probability pair. Each cache of the SI model allowing for random jumps contains 500 trials for each node, transmission probability pair.

The files updatebusinessresults.py, updatecompsciresults.py, and updatehistoryresults.py will add more runs of each epidemic simulation to the files in cache.

data

Contains the edge and vertex lists of the faculty hiring networks. Data was released under the CC BY-NC 2.0 license.

epidemic

The script epidemic.py describes the SI simulation we've implemented.

imports

The files importbusiness.py, importcompsci.py, and importhistory.py generate networkx networks and parse prestige metadata from the edge and vertex lists from data.

publications

The files called deep_learning_titles.txt, incremental_titles.txt, and topic_modeling_titles.txt contain the titles extracted under our choice of keywords for each topic. These titles have been selected from the computer science bibliography, dblp. This data is available under the Open Data Commons ODC-BY 1.0 license. The pickle files deep_learning.p, incremental.p, and topic_modeling.p contain the fraction of transmissions due to hiring under 10,000 permutation tests. The notebook spread_of_research_ideas.ipynb documents our permutation test.

results

Contains all of the plots from the paper. Code to generate these plots can be found in getplots.py. The file plot_utils.py has been reproduced from samplotlib under the BSD 2-Clause "Simplified" license.