Стереотипогенерувальний потенціал заголовків українських новинних інтернет-ресурсів для української молоді
Stereotype-Generating Potential of Ukrainian News Internet Resources Headlines for Ukrainian Youth

Summary/Abstract: Main objective of the study: to identify the facts of conscious or unconscious assistance in the formation of new stereotypes and supporting active stereotypes against different social groups, for instance, drug addicts, former prisoners, Romani people and sexual minorities, among Ukrainian youth in the headlines of leading domestic news Internet resources. Methodology: documentary data analysis method was used to: a) characterize modern youth as a specific group of mass media audiences; b) further interpretation of data on young Ukrainians' fears, preferences, expectations, values, etc. By the help of content analysis method, the potentially stereotypical markers in the titles of the analyzed Internet resources were identified and described. Results and conclusions: while making current study we relied both on open data about society and about young people, and based on this data Ukrainian high school pupils and students' stereotypes about several social groups, including drug addicts, Roma, former prisoners and members of sexual minorities were logically identified. Content analysis based on the method of continuous sampling of RBC.ua, Ukrainian Pravda and UNIAN resources' headlines of the first three weeks of May 2020 partly confirmed the hypothesis that Ukrainian online news mass media are able to generate and maintain their audience stereotypes, by the help of exceptional publishing news about these social groups. In general, we assessed the stereotype-generating potential of the studied media as negative. This is primarily because of following journalistic standards in the process of writing news reports extremely accurately. Significance: this research is significant for Ukrainian scientific thought because the author firstly proposed assessing the stereotype-generating potential of media texts algorithm.

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