Fake news spreading is strongly connected with the human involvement as individuals tend to fall, adopt and circulate misinformation stories. Until recently, the role of human characteristics in fake news diffusion, in order to deeply understand and fight misinformation patterns, has not been explored to the full extent. This paper suggests a human-centric approach on detecting fake news spreading behavior by building an explainable fake-news-spreader classifier based on psychological and behavioral cues of individuals. Our model achieves promising classification results while offering explanations of human motives and features behind fake news spreading behavior. Moreover, to the best of our knowledge, this is the first study that aims at providing a fully explainable setup that evaluates fake news spreading based on users credibility applied to public discussions aiming to a comprehensive way to combat fake news through human involvement.
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