Extract data from the "Share and Multiply" dataset for use with MGen.

Justin Tracey 3fc10e1441 add better docs 6 месяцев назад
hmm 338aead827 hmm: fix bug in parallel_run.sh preventing waiting 6 месяцев назад
src 88e3e914be nit: use default hashmap 6 месяцев назад
Cargo.toml 903b430b76 incorporate file sizes into message lengths 1 год назад
README.md 3fc10e1441 add better docs 6 месяцев назад

README.md

This repo contains tools to extract empirical distributions from the "Share and Multiply" (SaM) dataset of WhatsApp chat metadata.

More thorough documentation is coming soon, but the gist is:

  • Download the json_files.zip file they provide, and extract it somewhere.
  • Run the extract tool to pare and serialize the SaM data. (Using chat*.json in any of the following commands means using all available chats; you can use a subset for faster processing, so long as you're consistent.) cargo run --bin extract stats/ json_files/chat*.json
  • Use the tools in hmm to label messages as "active" or "idle".
    • install the dependencies via pip install -r requirements.txt
    • run the shell script to invoke the python script in parallel ./parallel_run.sh ../stats/ stats2/
  • Run the process tool to generate all empirical distributions other than message sizes. cargo run --bin process dists/ hmm/stats2/ json_files/chat*.json
  • Run the message-lens tool to generate distributions for message sizes. This takes an optional argument for file sizes (must be first if provided, sorry for the jank). If you have a source for file sizes, you can provide it here. If you don't want to simulate sending files, you can omit it. If you don't have a source, you can use the one we provide based on public WhatsApp groups in 2023. cargo run --bin message-lens -- -s data/file_sizes.dat dists/ json_files/chat*.json

At this point, dists/ will contain distributions ready for use in MGen, organized by the user being simulated.