@inproceedings{081b442433084ebd943dff55f84e180a,
title = "Are you influenced?: Modeling the diffusion of fake news in social media",
abstract = "We propose an approach inspired by the diffusion of innovations theory to model and characterize fake news sharing in social media through the lens of the different levels of influential factors (users, networks, and news). We address the problem of predicting fake news sharing as a classification task and demonstrate the potentials of the proposed features by achieving an AUROC of 0.97 and an average precision of 0.88, consistently outperforming baseline models with a higher margin (about 30% of AUROC). Also, we show that news-based features are the most effective at predicting real and fake news sharing, followed by the user- and network-based features.",
keywords = "diffusion of innovations theory, fake news sharing, information diffusion, misinformation",
author = "Abishai Joy and Anu Shrestha and Francesca Spezzano",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 13th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021 ; Conference date: 08-11-2021",
year = "2021",
month = nov,
day = "8",
doi = "10.1145/3487351.3488345",
language = "English",
series = "Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021",
pages = "184--188",
editor = "Michele Coscia and Alfredo Cuzzocrea and Kai Shu",
booktitle = "Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021",
}