论文标题
在Twitter上建模假新闻的传播
Modeling the spread of fake news on Twitter
论文作者
论文摘要
由于移动设备的使用越来越多以及互联网访问的增加，假新闻可能会对社会产生重大的负面影响。因此，必须开发一个简单的数学模型来了解假新闻的在线传播。在这项研究中，我们提出了一个在Twitter上传播假新闻的点过程模型。拟议的模型将假新闻项目的传播描述为一个两个阶段的过程：最初，假新闻作为普通新闻传播；然后，当大多数用户开始识别新闻项目的虚假性时，该项目本身就是另一个新闻故事。我们使用两个假新闻项目的数据集在Twitter上传播。我们表明，所提出的模型优于当前的最新方法，可以准确预测假新闻项目的传播的演变。此外，文本分析表明，我们的模型适当地渗透了更正时间，即Twitter用户开始意识到新闻项目的虚假性的那一刻。提出的模型有助于理解虚假新闻在社交媒体上传播的动态。它提取对传播模式的紧凑表示的能力可能有助于对假新闻的检测和缓解。
Fake news can have a significant negative impact on society because of the growing use of mobile devices and the worldwide increase in Internet access. It is therefore essential to develop a simple mathematical model to understand the online dissemination of fake news. In this study, we propose a point process model of the spread of fake news on Twitter. The proposed model describes the spread of a fake news item as a two-stage process: initially, fake news spreads as a piece of ordinary news; then, when most users start recognizing the falsity of the news item, that itself spreads as another news story. We validate this model using two datasets of fake news items spread on Twitter. We show that the proposed model is superior to the current state-of-the-art methods in accurately predicting the evolution of the spread of a fake news item. Moreover, a text analysis suggests that our model appropriately infers the correction time, i.e., the moment when Twitter users start realizing the falsity of the news item. The proposed model contributes to understanding the dynamics of the spread of fake news on social media. Its ability to extract a compact representation of the spreading pattern could be useful in the detection and mitigation of fake news.
