Abstract:
The current level of development of computational linguistics is characterized by the involvement of more and more complex levels of linguistic analysis in the field of automatic analysis, the use of hybrid approaches in solving computer text processing problems that combine machine learning and algorithmic methods. At the same time, the levels of complexity of modern text processing tasks, such as extracting time reference in a text, analyzing the structure of discourse and many others, require the active involvement of expert linguistic knowledge. Nowadays, learning a foreign language is the goal of a very large number of people. There are many tools, methods and techniques for self-development of a foreign language that can significantly increase the effectiveness of training. Currently, sentiment analysis is used in monitoring, analytical and alarm systems, as well as in document management systems and advertising platforms. At the same time, this technology is practically not used in foreign language teaching systems, although it has a huge untapped potential. Almost all currently existing applications for learning foreign languages do not use the ability to analyze the tonality of the text. Mastering the emotional vocabulary of a language is a difficult task for a student, so this aspect should be given special attention. This paper is devoted to the description of a web application developed by us for learning German language, which is based on the use of sentiment analysis. This solution can be extended to other foreign languages as well.
