All code for the publication submitted to the ESD:SI on social tipping.
by Jordan Everall, Jonathan F Donges Ilona M Otto
This paper has been submitted for publication in Earth System Dynamics: Special issue on tipping points
In this project, we conduct a literature review and intercomparison of modelling and empirical results in order to identify general trends in social tipping dynamics on social networks. Specifically we look at what fraction of a given social group has to engage with a specific norm in order to result in rapid, system wide norm changes.
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Ssteady state fraction of tipped individuals vs the fraction of individuals at or around a potential tipping point for various simulation and experimental results |
The compiled datasets to produce all figures in the manuscript are located in the Compiled
folder.
Data used to make the main figures Fig. 6 and Fig. 7 in the manuscript are in Tipping_threshold_plot.csv
and Tipping_points_fin_merged_1.csv
respectively.
Figures 4 and 5 are made with The Pareto effect in tipping social networks Tipping Data - Tipping_Data
. Data for Table 4. are in The Pareto effect in tipping social networks Tipping Data - Sheet_main_fig.csv
.
All source code used to generate the results and figures in the paper are in
the Analysis
and Figures
folders respectively. Please email me (Jordan) if there are any questions as some scripts and data are still incomplete and some cleaning is still required
You can download a copy of all the files in this repository by cloning the git repository:
git clone https://github.com/foroveralls/pareto_tipping.git
or [download a zip archive]https://github.com/foroveralls/pareto_tipping/archive/refs/heads/master.zip.
This project is open-source, and the data is made available under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license. By using or referencing the data in this repository, you agree to comply with the license terms outlined below.
License Information: The data in this repository is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means you are free to:
- Share: Copy and redistribute the material in any medium or format.
- Adapt: Remix, transform, and build upon the material for any purpose, even commercially.
Under the following conditions:
- Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.