Are you influenced?: modeling the diffusion of fake news in social media
Are you influenced?: modeling the diffusion of fake news in social media
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DOI：
10.1145/3487351.3488345
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发表时间：
2021-11
期刊：
影响因子：
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通讯作者：
Abishai Joy;Anu Shrestha;Francesca Spezzano
中科院分区：
文献类型：
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作者：
Abishai Joy;Anu Shrestha;Francesca Spezzano
我们提出了一种受创新扩散理论启发的方法，通过不同层次的影响因素（用户，网络和新闻）的透镜来建模和表征社交媒体中的假新闻共享。我们将预测假新闻共享作为一项分类任务来解决，并通过实现0.97的AUROC和0.88的平均精确度来展示拟议特征的潜力，以更高的裕度（约为AUROC的30%）始终优于基线模型。此外，我们发现，基于新闻的功能是最有效的预测真实的和假新闻共享，其次是基于用户和网络的功能。
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.