RDMSC

Source code for the Information Sciences paper "Rumor Detection on Social Media through Mining the Social Circles with High Homogeneity"

Requirements

Code developed and tested in Python 3.9 using PyTorch 1.10.2 and Torch-geometric 2.2.0. Please refer to their official websites for installation and setup.

Some major dependencies are as follows:

certifi==2023.5.7
charset-normalizer==3.1.0
colorama==0.4.6
contourpy==1.0.7
cycler==0.11.0
emoji==2.2.0
fonttools==4.39.4
idna==3.4
importlib-resources==5.12.0
joblib==1.2.0
kiwisolver==1.4.4
MarkupSafe==2.1.2
matplotlib==3.7.1
numpy==1.24.3
packaging==23.1
pandas==2.0.1
Pillow==9.5.0
psutil==5.9.5
PyMySQL==1.0.3
pyparsing==3.0.9
python-dateutil==2.8.2
pytz==2023.3
requests==2.30.0
scikit-learn==1.2.2
scipy==1.10.1
six==1.16.0
threadpoolctl==3.1.0
tqdm==4.65.0
typing_extensions==4.5.0
tzdata==2023.3
urllib3==2.0.2
zipp==3.15.0

Datasets

Data of Twitter15 and Twitter16 social interaction graphs follows this paper:

Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang. Rumor Detectionon Social Media with Bi-Directional Graph Convolutional Networks. AAAI 2020.

The raw datasets can be respectively downloaded from https://www.dropbox.com/s/7ewzdrbelpmrnxu/rumdetect2017.zip?dl=0.

User information was crawled by the Twitter developer tool Tweepy around February 2022, when restrictions were not particularly strict. twitter15_User_Information.csv, Twitter15_User_Friends.csv and Twitter15_Ego_ Relationships.csv represent user information, friend information, and connections between them, respectively. The meaning of each field in the tables can be found as follows:

https://developer.twitter.com/en/docs/twitter-api/v1/data-dictionary/object-model/user.

In order to meet Twitter's privacy protocol, we have removed some fields and limited the number of friends per user.

Run

# Data pre-processing
python ./utils/getInteractionGraph.py Twitter15
python ./utils/getInteractionGraph.py Twitter16
python ./utils/getEgoGraph.py Twitter15
python ./utils/getEgoGraph.py Twitter16
# run
python RDMSC_Run.py

Citation

If you find this repository useful, please kindly consider citing the following paper:

@article{ZHENG2023119083,
title = {Rumor detection on social media through mining the social circles with high homogeneity},
journal = {Information Sciences},
volume = {642},
pages = {119083},
year = {2023},
issn = {0020-0255},
doi = {https://doi.org/10.1016/j.ins.2023.119083},
url = {https://www.sciencedirect.com/science/article/pii/S0020025523006680},
author = {Peng Zheng and Zhen Huang and Yong Dou and Yeqing Yan},
keywords = {Rumor detection, Social media, Social circles, Homogeneity}
}