- python2.7 or python3.7
- sklearn, pandas, networkx, numpy
- path:
ICI/datasets/ - sources for raw data: Digg, Twitter.
- data preprocessing scripts:
clean_diggs.py;clean_twitter.py - preprocessed datasets:
[filename].edgelist;[filename].seed;[filename].spread
- path:
ICI/utils/
- command:
python benchmark.py [--model model_name] [--dataset file_name] [--output 0/1] [--repeat simulation_times] [--step spread_in_each_step] [--beta ICI_param] [--gamma ICI_param];
- example:
python benchmark.py --model ici --dataset digg --output 1 --repeat 1000 --step 10 --beta 0.9 --gamma 0.6;
-
Input arguments
- datasets:
--dataset={"digg","twitter"} - support models:
--model={"ic", "icm", "icn", "icr", "lt", "ftm", "ltc"} - output mode: print all results by
--output 1
- datasets:
@inproceedings{ici,
author = {Shiqi Zhang and
Jiachen Sun and
Wenqing Lin and
Xiaokui Xiao and
Yiqian Huang and
Bo Tang},
title = {Information Diffusion Meets Invitation Mechanism},
booktitle = {Companion Proceedings of the {ACM} on Web Conference 2024, {WWW} 2024,
Singapore, Singapore, May 13-17, 2024},
pages = {383--392},
publisher = {{ACM}},
year = {2024}
}