Detection of Fake News based on readability

Social media has become one of the principal sources of news consumption, one of their properties is the speed in which the content is created and spread, but the content is not always verified by the users before they share them. This have made easy to generate intentionally false content, there exists different approaches to tackle the detection of fake news mostly of which use English texts for the analysis. We take these works as a basis to analyze and propose some attributes useful in the detection of fake news in Spanish, there exists differences in the way in which the fake news content is generated between language because of the cultural differences and the target audience. We make use of properties of the texts as readability metrics to analyze the difference between content generated by professional journals and not recognized webs, and as a social media approach we use Twitter to analyze how the content is spread between users of this social network.