  This paper analyses two hitherto unstudied sites sharing state-backed
disinformation, Reliable Recent News (rrn.world) and WarOnFakes
(waronfakes.com), which publish content in Arabic, Chinese, English, French,
German, and Spanish. We describe our content acquisition methodology and
perform cross-site unsupervised topic clustering on the resulting multilingual
dataset. We also perform linguistic and temporal analysis of the web page
translations and topics over time, and investigate articles with false
publication dates. We make publicly available this new dataset of 14,053
articles, annotated with each language version, and additional metadata such as
links and images. The main contribution of this paper for the NLP community is
in the novel dataset which enables studies of disinformation networks, and the
training of NLP tools for disinformation detection.
