Abstract
Today, in the age of the information society, the media play a powerful role in shaping and influencing public opinion. Accordingly, it is a social phenomenon, which affects the point of view of the society. Now all information can be found in text form on the Internet, especially with the help of social media resources. Implementation of such relevant information technology as content analysis is the best way to analyze such kind of data. This method studies documents in their social context and it is used when examining the thematic orientation of the media. At the same time, thanks to the development of methods of content analysis, now it is possible to automatically study the content of different texts, their effectiveness and assess the impact on society. This study analyses existing approaches, methods and tools for content analysis and justifies the relevance of exploring the use of a wide range of linguistic categories for qualitative content analysis. Conceptual possibilities of using this type of analysis in modern linguistic and social research are also considered. The article shows the use of qualitative content analysis methods, based on the use of machine learning approaches and the developed three-language dictionary of criminally colored terms, which is one of the main tools for examining the distribution of criminally significant information of web media news sites by geographical, time characteristics and categories of crime. In this study, we also offer the bases of the development of content analysis information technology of news web space of certain geographical regions that are analyzed in time dependence on the given topic, namely criminal picture of the region. The texts of news sites of Kazakhstan, Ukraine, Great Britain and the USA were assembled automatically using the developed software product. They are considered as an experimental corpus.
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