This is the code and the dataset for the paper titled
If you end up using this code or the data, please cite our paper:
@inproceedings{Chetan:2019:CRD:3289600.3291010,
author = {Chetan, Aditya and Joshi, Brihi and Dutta, Hridoy Sankar and Chakraborty, Tanmoy},
title = {CoReRank: Ranking to Detect Users Involved in Blackmarket-Based Collusive Retweeting Activities},
booktitle = {Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining},
series = {WSDM '19},
year = {2019},
isbn = {978-1-4503-5940-5},
location = {Melbourne VIC, Australia},
pages = {330--338},
numpages = {9},
url = {http://doi.acm.org/10.1145/3289600.3291010},
doi = {10.1145/3289600.3291010},
acmid = {3291010},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {blackmarket, collusion, online social networks, retweets, twitter},
}
- Python 3.5.x To install the dependencies used in the code, you can use the requirements.txt file as follows -
pip install -r requirements.txt
First cd code and then run the corerank.py as follows -
python corerank.py
This will generate rankings for the tweets and users present in the Graph as present in the paper.
Provide appropriate paths for data files and parameters in constants.py.
If you face any problem in running this code, you can contact us at aditya16217[at]iiitd[dot]ac[dot]in or brihi16142[at]iiitd[dot]ac[dot]in or hridoyd[at]iiitd[dot]ac[dot]in
Copyright (c) 2019 Aditya Chetan, Brihi Joshi, Hridoy Sankar Dutta, Tanmoy Chakraborty
For license information, see LICENSE or http://mit-license.org
