  The rapid dissemination of misinformation through online social networks
poses a pressing issue with harmful consequences jeopardizing human health,
public safety, democracy, and the economy; therefore, urgent action is required
to address this problem. In this study, we construct a new human-annotated
dataset, called MiDe22, having 5,284 English and 5,064 Turkish tweets with
their misinformation labels for several recent events between 2020 and 2022,
including the Russia-Ukraine war, COVID-19 pandemic, and Refugees. The dataset
includes user engagements with the tweets in terms of likes, replies, retweets,
and quotes. We also provide a detailed data analysis with descriptive
statistics and the experimental results of a benchmark evaluation for
misinformation detection.
