/ASDIP

Primary LanguagePython

Adaptive Sampling-based Dynamic Graph Learning for Information Diffusion Prediction

This is the implementation of ASDIP: [Adaptive Sampling-based Dynamic Graph Learning for Information Diffusion Prediction].

Requirements

  • python == 3.9.18
  • pytorch == 2.0.1
  • numba == 0.55.1
  • numpy == 1.21.6
  • pandas == 2.0.3
  • scikit-learn == 1.3.0
  • dgl == 1.1.2
  • tqdm
  • wandb

Dataset

  • Download the preprocessed dataset from Baidu Yun （extract code nihb）
  • create a directory ./data/dynamic and put the downloaded dataset into the directory.

Run

Create the directories to store the running results

mkdir log results saved_models

Running command

#Memetracker
python train_ASDIP.py --prefix std --dataset douban --gpu 0 --causal before after none
#Douban
python train_ASDIP.py --prefix std --dataset memetracker --gpu 0 --causal before after none
#Weibo
python train_ASDIP.py --prefix std --dataset weibo --gpu 0 --causal before after none