This repository contains the code and data required to run the analyses in this paper.
- `datasets/` contains the data analyzed in our experiments. The file `aamas_2021.csv` is sourced from https://www.preflib.org/dataset/00037. The file `wu_tensor_data.pl` is sourced from https://github.com/facebookresearch/secure-paper-bidding (Wu et al., 2021). The other files are constructed by the scripts `construct_authorships.py` and `synthesize_aamas_text.py`, which have additional data dependencies not included in this repository.
- `clique_eval.py` runs the exact clique-counting analyses. Before running this, run the script `compile_count_cliques_c.sh` to compile the C++ subroutines.
- `detection_eval.py` runs the detection algorithm analyses. Code for detection methods TellTail and Fraudar was sourced from (Hooi et al., 2020) and (Hooi et al., 2016) respectively.
- `success_eval.py` runs the colluder success analyses. 
In all scripts, the argument "aamas_sub3" refers to the AAMAS dataset and the argument "wu" refers to the S2ORC dataset. Other arguments specify the setting (unipartite/bipartite), size and density parameters, detection method, etc.
