This project aims to highlight global discrepancies in the multilateral negotations towards a legally binding instrument on autonomous weapons through the Convention on Certain Conventional Weapons' Group of Governmental Experts (CCW/GGE) on LAWS.
It generates various data analyses related to the CCW/GGE. It includes Python and R scripts to process and visualize data on civil society participation, regional distribution, and other relevant statistics.
What if we could build more tools to analyse multilateral negotiations on top of this? Contribute in this repository or reach out for future projects.
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Download the transcripts from the UNOG website: https://conf.unog.ch/digitalrecordings/en
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Parse the data (algorithm publicly available soon);
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Clone the repository:
git clone https://github.com/yourusername/ccw-gge_factsheet.git
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Add a srcs folder with the input you want before running the functions;
• 3_longest_durations.py: Analyzes the longest durations related to certain activities.
• civil_society_time.py: Processes and visualizes data on civil society participation.
• hcp_count.py: Counts High Contracting Parties (HCP) and generates relevant statistics.
• statements_distribution.py: Visualizes the distribution of statements across various categories.
• statements_distribution.r: R script for analyzing the distribution of statements.
• region_distribution_graph.r: Generates regional distribution graphs.
• text_tidier.r: organizes statements to extract most common words.
• word_frequency.r: generates list of most 50 most frequent words.
• words_parser.py: removes duplicates from most frequent words list.
• word_cloud_gen.r: generate word cloud from parsed most frequent words list.
Contributions are welcome!
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