  With the digitization of media, an immense amount of news data has been
generated by online sources, including mainstream media outlets as well as
social networks. However, the ease of production and distribution resulted in
circulation of fake news as well as credible, authentic news. The pervasive
dissemination of fake news has extreme negative impacts on individuals and
society. Therefore, fake news detection has recently become an emerging topic
as an interdisciplinary research field that is attracting significant attention
from many research disciplines, including social sciences and linguistics. In
this study, we propose a method primarily based on lexicons including a scoring
system to facilitate the detection of the fake news in Turkish. We contribute
to the literature by collecting a novel, large scale, and credible dataset of
Turkish news, and by constructing the first fake news detection lexicon for
Turkish.
