The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/6ca3d747-ac81-4571-be33-af1948b0dfba

Schubotz, Lukas (2024): Data Underlying Opinion Dynamics poster at ESSA in Glasgow in 2023. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/6ca3d747-ac81-4571-be33-af1948b0dfba.v2

Dataset

x choose version: version 1 - 2024-02-15

• Climate and Climate Change
• Environmentally Sustainable Energy Activities
• Policy and Administration
• Energy
• Studies in Human Society
• Environment

agent-based modelling, energy transition, inverse modelling, opinion dynamics

2022-2023

CC BY-SA 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Lukas Schubotz

The data are aggregated opinion averages over time of polls on a 5-point scale concerning questions about climate change and the energy transition. This is the data repository for the poster I made for the ESSA conference in Glasgow 2023. My aim with this was to get a first grip on inverse modelling and share what I have learned with the community. I'm happy to share the poster for more context and content upon request via lschubotz@tudelft.nl. The code I've used this data for is available on the TU Delft GitLab. I gratefully acknowledge the support of Populytics in this research project who provided the data. Here, I provide the aggregated data as it went into the model. Column 1 is the time stamp, column 2 is the value I used, the latter being the aggregated mean value of the votes during that time stamp.

• 2024-02-15 first online

• 2024-03-06 published, posted

4TU.ResearchData

.csv

TU Delft, Faculty for Technology, Policy, and Management, Energy Transition Lab