# PoP-net A novel popularity prediction network (PoP-Net), which consists of two branches for dealing with evolutional patterns of cascades and interactions between users respectively, for online content.

TCSE-Net

TCSE-Net is a implemention of paper 'Trend and cascade based spatiotemporal evolution network to predict online content popularity', which has been published in Multimedia Tools and Applications.paper

Dependency Package

python 3.6

pytorch 1.7.1

File Description

data_preprocess is used to process the raw data as the train data.

PoPnet_model contains the pytorch implementation of PoP-net.

Datasets

The datasets we used in our paper are Sina Weibo and Twitter. For the Sina Weibo dataset, you can download https://github.com/CaoQi92/DeepHawkes and the Twitter dataset is avilable https://github.com/majingCUHK/Rumor_RvNN.

##Steps to run PoP-net 1.process the raw data cd data_preprocess python preprocess_graph_signal.py #you can configure parameters and filepath in the file of "config.py" 2.trainsform the datasets to the format of ".pkl" command: pyhton data_pretreat.py

cd PoPnet_model python main.py

If you find this code useful, please let us know and cite our paper.