Interpretation of the implicit modality: Semiotic markers of the speech intentions in the texts of online communication

Abstract

The authors of this article present the results of the psycho-linguistic stage of studies which aim to develop instruments for automated identification of online communication texts according to a set dictum and modus parameters. The intentional, volitional, and emotional content of the texts was analyzed which determines their genre and linguo-semiotic peculiarities. As a result of an introspective analysis of the content of texts on the topic of a professional crisis, a number of communicative-textual categories were identified that are significant from the point of view of diagnosing the psychological state of the subject of speech. A description is given of both segment markers of subjective meanings — predicates that directly reflect the intentional-volitional state of the speaker and text fragments that, not being direct modus indicators, with a high degree of probability refer in this context to a certain internal state of the author text. The well-known discursive conventions are taken into account. Methodologically, the authors are guided by the theoretical guidelines of the concept of stylistic-speech consistency (M. N. Kozhina) and the model of relational-situational analysis developed within the framework of the theory of artificial intelligence by G. S. Osipov. When analyzing the modus-dictum content of texts, a scenario approach and methods of “internal and external reconstruction” of subjective meanings were used, interpreted with reference to both segment markers within the analyzed text unit (utterance), and their connections with such adjacent (external) text fragments, which, in the context of a network discussion, refer to certain intentional-volitional states of the subject of speech and are, in fact, their semantic anaphors. It is shown that the content of texts on the subject of a professional crisis is characterized by a high degree of emotiveness, the automatic “reading” of which is an important task of computer linguistics and artificial intelligence.