  Nowadays, Internet is a primary source of attaining health information.
Massive fake health news which is spreading over the Internet, has become a
severe threat to public health. Numerous studies and research works have been
done in fake news detection domain, however, few of them are designed to cope
with the challenges in health news. For instance, the development of
explainable is required for fake health news detection. To mitigate these
problems, we construct a comprehensive repository, FakeHealth, which includes
news contents with rich features, news reviews with detailed explanations,
social engagements and a user-user social network. Moreover, exploratory
analyses are conducted to understand the characteristics of the datasets,
analyze useful patterns and validate the quality of the datasets for health
fake news detection. We also discuss the novel and potential future research
directions for the health fake news detection.
