Lexical Expressive Means and Stylistic Devices
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19 Alba-Juez L, Larina TV (2018) Language and emotion: discourse-pragmatic perspectives. Russ J Linguist 22(1):9–37. 40 CONCLUSION In my conclusion, the analysis of emotive lexemes collected from different online media sources made it possible to investigate various emotional expressions used in the Internet media. The selection was carried out according to the classical criteria of emotivity. The study results showed how quite different and quite mixed expressive processes can construct the meaning of the message and influence the reader. The texts of the selected online media are characterized by multimodality, polyphony, hypertextuality, heterogeneity, and carry bifurcated denotational meaning. It was revealed that these forms are predominantly the most expressive emotive process. The present study recognized and described emotive lexical units, analyzed the different layers of information that make up the emotionality of a media text and determine the conditions of the described lexical units’ functioning. The pattern markers that are present in the text and influence textual variations were also studied. To conclude, multimodality was also considered, which characterizes media writing. This research shows that expression of feelings and emotions in a digital discourse requires special linguistic and extra-linguistic means. Online media are a place where people can express themselves freely. Hence, it can be said that media favor self-expression. Content writers have the freedom to integrate any expressive process. Unlike the traditional written discourse, where affective categories are often channeled through lexicon, the digital space is associated with the presence of linguistic and extra-linguistic layers. This study identified lexical and linguistic means that integrate emotions into the online media texts. Those expressive processes are a function of the immediacy and spontaneity of media discourse. Basic emotive vocabulary and possible extra-linguistic elements actualized in Kazakh media discourse appeared to exploit paraverbal expressions to replace expressive means used in face-to-face communication. Such tactics allow conveying emotions in written debates. When it comes to digital media texts, it is not enough to look at what has been said. Attention should be paid to both linguistic and non-linguistic processes. Depending on the purpose of the media 41 text, content writers who seek to influence readers can use emotive lexemes in specific ways. Therefore, it is important to examine emotive language from the standpoint of linguistics and extra-linguistics. The results of this study can be used in teaching aids and courses in philology, psychology, journalism, and semiotics. Overall, in this study we focused on how and to which extent affective connotations of very basic textual measures at the lexical, inter-lexical, and even sublexical level of a poem—that can all be derived from existing normative databases—determine the perception of the general affective meaning of poetry in a way that proves quantifiable beyond the specific context of a given poem, author, or recipient. By applying an exhaustive exploratory regression analysis to a comprehensive corpus of poems and their ratings from hundreds of readers, we found that a significant amount of variance in discrete and dimensional affective ratings of poetry can be accounted for solely by text-based affective measures from different levels of processing. In. conclusion, in all of the presented statistical models—focusing on different aspects of the general affective meaning—variance of each rating dimension is significantly accounted for by affective properties of several text levels: while the lexical one generally explains the biggest amount of variance, further significant effects in explaining residual variance are found for the alternative sublexical and inter-lexical text levels. Thus, our research brings together previous accounts on specific effects of single text levels, showing how they may co-exist each in their own right or interact to constitute the complex holistic framework of poetry perception. Taken together, the affective properties of text elements from all three text levels could account for 43–70% of the variance in the perceived general affective meaning of the here utilized poetry and still for 23–48% of the variance in further aesthetic and onomatopoetic evaluations of the poems—a substantial amount purely accounted for by textual elements which should not be neglected in future affective analyses of poetry. |