Intelligent Legal Decision Support System to Classify False Information on Social Media

In the study, a decision support system for governance in the field of law was developed and the existing decision making model to conduct linguistic expertise of inaccurate public information in online media and social networks was improved, taking into account the human factor. The results of the proposed system are presented in a set of the formed recommendations, based on which the user makes a decision. The specific feature of the decision support system (DSS) is that it works with several types of false information in accordance with the Russian legislation against “fake news” addressed in the study. The adapted algorithms of Bayes classification were studied and built for effective work of the decision-making and classification module of false information. These algorithms were implemented in the system and a computational experiment on text classification was performed. The study examined the features of the Russian legislation on false information dissemination, and described the components and functionality of the proposed intelligent legal DSS, as well as its efficiency. This solution implies a widespread use of systems, application packages, special software and legal support for analytical work, obtaining forecasts and conclusions on the processes under study based on databases and expert judgment, considering the human factor and active influence of the controlled system on the governance process.