The qualitative analysis of information messages and the assessment of publications on the Internet are becoming more urgent than ever. A large number of materials are published on the Internet on various events in the world; the nature of these publications can affect the political and social life of society. In order to ensure the safety of the population of the Russian Federation and meet the requirements of regulatory documents, a methodology for mediametric information analysis with the use of machine learning algorithms is proposed. Based on the results of research in this area, the main approaches to mediametric information analysis are determined. An approach is proposed for determining the sentiment of publications using the Word2Vec model and machine learning algorithms for natural language processing. A methodology is formulated that takes into account the technical features of a publication source and the existing methods of mediametric information analysis. On the basis of real information publications, the results of the implementation of the methodology of mediametric analysis and determination of the sentiment of messages are presented.
Methodology of Mediametric Information Analysis with the Use of Machine Learning Algorithms