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With the advent of modern day journalism and social media at peak, fake news may spread faster around the world. Therefore, it is important to detect the fake news and considered as a popular research topic among the community.Any changes on a particular news articles includes editorial, news report, expose, etc are predicted by using Fake News Detection (FND) techniques. Nowadays, fake news is defined as one of the major threats to economies, democracy and journalism.But, the reliability identification of online information is the most important difficult process in FND, which leads the researchers and technical developers to design an efficient techniques for improving the FNDs' performance. In this study, a discussion for detecting fake news on social media, including different kinds of news platforms, fake news characterizations, different types of data for fake news and finally, existing algorithms from a data mining perspective. In addition, the study also presents the open research problems for FND on social media.
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