Android App for Determining Reliability of News

In today's rapidly changing digital world, the problem of spreading false information, or "fake news", is becoming increasingly urgent, having a negative impact on both individuals and society as a whole. This work is devoted to the development of a system designed to identify and verify the authenticity of media content. The system is based on machine learning algorithms, data processing methods and distributed systems technologies. Using modern algorithms, it is able to analyze content in various formats, thereby increasing the accuracy and speed of detection. As part of the final qualification work, a comprehensive system was developed, consisting of a client application and a server part. The client part is represented by a mobile application created using modern user interface development methods. The server part is implemented using several programming languages, providing support for machine learning models and based on modern web technologies. Communication between the elements of the system is carried out through synchronous and asynchronous methods, including the use of modern messaging technologies. Keywords: fake news, machine learning, text classification, media content analysis, data processing, microservice architecture, microservices, Android, Kotlin, C#, Python, gRPC, Apache Kafka.