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