ArXiv Preprint
Misinformation spread in online social networks is an urgent-to-solve problem
having harmful consequences that threaten human health, public safety,
economics, and so on. In this study, we construct a novel dataset, called
MiDe-22, having 5,284 English and 5,064 Turkish tweets with their
misinformation labels under several recent events, including the Russia-Ukraine
war, COVID-19 pandemic, and Refugees. Moreover, we provide the user engagements
to the tweets in terms of likes, replies, retweets, and quotes. We present a
detailed data analysis with descriptive statistics and temporal analysis, and
provide the experimental results of a benchmark evaluation for misinformation
detection on our novel dataset.
Cagri Toraman, Oguzhan Ozcelik, Furkan Şahinuç, Fazli Can
2022-10-11
