Evons：用于假新闻和真新闻病毒性分析和预测的数据集
Evons: A Dataset for Fake and Real News Virality Analysis and Prediction
摘要：
我们提出了一个新的收集新闻文章来源于假的和真实的新闻媒体来源的分析和预测的新闻病毒式传播。与现有的包含声明或新闻文章标题和正文的假新闻数据集不同，在这个集合中，每篇文章都支持Facebook参与计数，我们认为这是文章病毒式传播的指标。此外，我们还提供了文章描述和缩略图与文章在Facebook上共享。这些图像被自动标注了对象标签和颜色属性。使用基于云的视觉分析工具，缩略图图像也被分析用于面部，并且用面部属性注释检测到的面部。我们实证研究使用此集合的文章病毒式预测的一个示例任务。
英文摘要：
We present a novel collection of news articles originating from fake and real news media sources for the analysis and prediction of news virality. Unlike existing fake news datasets which either contain claims or news article headline and body, in this collection each article is supported with a Facebook engagement count which we consider as an indicator of the article virality. In addition we also provide the article description and thumbnail image with which the article was shared on Facebook. These images were automatically annotated with object tags and color attributes. Using cloud based vision analysis tools, thumbnail images were also analyzed for faces and detected faces were annotated with facial attributes. We empirically investigate the use of this collection on an example task of article virality prediction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
