  The rapid increase in fake news, which causes significant damage to society,
triggers many fake news related studies, including the development of fake news
detection and fact verification techniques. The resources for these studies are
mainly available as public datasets taken from Web data. We surveyed 118
datasets related to fake news research on a large scale from three
perspectives: (1) fake news detection, (2) fact verification, and (3) other
tasks; for example, the analysis of fake news and satire detection. We also
describe in detail their utilization tasks and their characteristics. Finally,
we highlight the challenges in the fake news dataset construction and some
research opportunities that address these challenges. Our survey facilitates
fake news research by helping researchers find suitable datasets without
reinventing the wheel, and thereby, improves fake news studies in depth.
