  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.
