# 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 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
python 3.6
pytorch 1.7.1
data_preprocess is used to process the raw data as the train data.
PoPnet_model contains the pytorch implementation of PoP-net.
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