Restoration Discourses on Twitter

List of code scpripts (Goolge Colab Jypter Notebook)
[code]:

1. statics_summary_plots.ipynb: statistic summary of the landscape restoration-related tweets
2. topics_BERT.py: Python script for topic modeling with BERTopic
3. topics_over_time.py: Python script for topic modeling with time
4. tweets_country_assignment.ipynb: assign country information to each Twitter user
5. Ludwig_treeplanting_classifer.ipynb: text classifier for tree planting-related tweets
   [data]: datasets for training and testing
   [model]: Ludwig model configuration files

List of figures produced from this project
[figures]:

1. Figure 1-8: Figures in the main text
2. Figure A-M: Figures in the appendix