Readers’ interest in the structural components of the scientific Internet text: The experience of multimodal research

The article presents the results of an experiment aimed at determining the characteristics and objects of user interest in the elements of a scientific Internet text as a sign of active perception of its content and correct understanding. User interest is treated in the article as a direct marker of active perception of scientific Internet text and can be understood as a condition of correct understanding of the content of the material. On the basis of the multimodal approach and the author’s complex methodology (experiment using videoculographic analysis, UXmethodologies, semi-structured interview and comparative analysis) the data on operational user actions in relation to the text and verbal reflection on its content and formal properties were obtained, which made it possible to draw conclusions about the peculiarities of perception and understanding of the text by different groups of users. The article discusses the nature of the effects of affordances on the algorithms for working with the content of the text. The authors conclude about the correlation between the nature of interaction with the scientific Internet text, the user’s precedent experience and some material and semiotic properties of the text. The greatest interest of users is illustrations syncretically integrated into the text of the article, and pop-up comments that explain or clarify semantic fragments of the text or complex terminology. The smallest interest for readers is the annotation of the article and keywords. The authors conclude about the conservative scenario of digital reading of scientific articles, in which users mainly expect such elements of a scientific Internet text as annotations and keywords to be embodied like the “offline”. The authors formulate the hypothesis that the semantic effects that occur because of the performing or imperfect of operational actions can vary from the features of the focus of interest to constructing a specific semantic model of the perceived text.