Matrix classification of aerospace-themed media text headlines: applied research and effectiveness analysis

this article is dedicated to the applied research of the effectiveness of matrix classification of media text headlines, focused on aerospace themes. The study begins with an analysis of the functions and roles of headlines within the structure of media texts. The article examines the evolution of the headline's function from purely informative to a tool for capturing the reader's attention and shaping emotional perception, emphasizing the increasing importance of headlines in the context of information overload. To confirm the significance of the headline, a statistical study based on a survey of 100 respondents is presented, demonstrating the substantial impact of headline attractiveness on the decision to read the material. The article thoroughly analyzes two key characteristics of an effective headline: synsemanticity (connection to the content of the text) and autosemanticity (independent significance and attractiveness). Furthermore, an original matrix for classifying headlines is proposed, dividing them into types (objective and subjective) and categories (character-based, locative, temporal, situational, subject-based, form-indicating, generalizing, evaluative). The application of this matrix is demonstrated through examples of aerospace-themed headlines, allowing for the identification of specific features in their construction and determining the objectivity passport of the information source. In conclusion, the study summarizes the findings, demonstrating the effectiveness of the proposed matrix for systematizing the analysis of headlines and identifying trends in the coverage of aerospace themes in the media space, opening up prospects for further research and the development of effective media communication strategies in this field.

media text, headline, aerospace themes, matrix classification, synsemanticity, autosemanticity, communication strategies, information space