The potential of emotive language to influence the understanding of textual information in media coverage

The study examines how emotive language in Kazakh online media shapes readers’ understanding and public relations. With the rise of Internet-mediated communication—used by an estimated 57% of the global population—new discursive practices have emerged, emphasizing immediacy, spontaneity, and user participation. The research problem centers on identifying and analyzing emotive lexical means in Kazakh media discourse and assessing their impact on readers’ cognitive perception of news. The purpose is to map emotive vocabulary usage across major Kazakh online media and to understand its role in influencing audience attitudes within media texts characterized by functionality, communicativeness, content, and intentionality. The study argues that emotivity is integral to media discourse and that linguistic subjectivity expressed through emotive lexemes can influence decision making and public engagement, making its analysis important for media communication and journalism.

The literature frames online media as privileged, real-time spaces fostering new forms of expression and multimodal discourse. Scholars highlight the emergence of a digital language emphasizing extra-linguistic units and expressive devices. Prior research notes the complexity of media texts—plurisemiotic, multimodal, and highly expressive—and emphasizes that linguistic analysis should extend beyond semantics to phonology, morphology, syntax, and stylistics to capture how expressive components interact. Gaps identified include challenges due to the freedom and spontaneity of online communication and technical limitations in analysis. The review positions emotive vocabulary at the intersection of linguistics, anthropology, psycholinguistics, and discourse studies, noting persistent conceptual ambiguities among related terms (subjectivity, affectivity, feeling, emotion). The study seeks to contribute by focusing on emotive lexicon in media discourse, its combinatorics, and its role in text construction, engaging with frameworks such as Van Dijk’s socio-cognitive perspective and prior work on affective lexemes and multimodality.

The study analyzes emotive vocabulary in Kazakh online media through a contextual and cognitive approach using a heterogeneous corpus from three top sources: Zakon.kz (politics/news), Kazinform (world/news/entertainment), and Sputnik Kazakhstan (general themes including show business, celebrity life, cuisine, tourism). Data were collected between October 2020 and May 2021. A total of 23,894 media texts (threaded messages including questions and replies) were collected manually via copy-paste, with context omitted to focus on lexeme-level analysis; participants remained anonymous to adhere to ethical standards of autonomy and anonymity. A mixed-methods approach combined automated emotive-semantic analysis with manual verification. The Tropes software (with Emotaix scenarios) was used for stylistic, syntactic, and semantic analysis to identify and classify emotive/affective lexicon by valence and topic, leveraging semantic meta-categories and allowing for syntactic flexibility (literal/figurative usage). Tropes categorized content using fuzzy logic and computed frequency of emotive item occurrences. Extracted keywords and semantic classifications were then subjected to linguistic and qualitative analysis to determine contexts and align emotive items with a standard classification of emotions (primary/secondary; explicit/implicit expression), as well as to examine their referential (cognitive, emotional, behavioral) components following Van Dijk’s three-component dimension. Quantitatively, frequencies of emotive units were tallied to identify the most prevalent lexemes and their emotional categories. Raw Tropes outputs were not included due to cumbersomeness.

- Emotivity in Kazakh media texts is conveyed through both lexical and syntactic means and is pivotal in shaping public relations and influencing audiences. - The emotive lexicon is multidimensional and complex, spanning nouns, verbs, adjectives, adverbs, phrases, and sentences; expressions can be explicit or implicit. Primary emotions identified are joy, sadness, fear, and hope, with complex emotions deriving from simpler ones (e.g., terror includes panic, fear, fright, concern, anxiety). - Platform-specific emotion profiles: Zakon.kz (politics-oriented) is dominated by negative emotions—especially sadness and fear; Kazinform (news) commonly shows fear and joy; Sputnik Kazakhstan (general/entertainment) features joy and hope. Overall, positive emotions tend to prevail in entertainment-oriented sources. - Culture of Internet media readers appears to play a decisive role in perception of communication products, interacting with other variables. - Emotive item usage depends on discourse content and writer intentions, with varied reportage/manipulation tactics according to coverage. - The study cataloged affective categories and standard emotion markers (per Van Dijk’s cognitive, emotional, behavioral components) and provided examples across parts of speech; it identified core affective lexemes central to combinatorial patterns. - Corpus: 23,894 texts collected from October 2020 to May 2021 across three leading Kazakh online media outlets.

Findings support the premise that emotions and cognition are interrelated and that emotive vocabulary functions as a persuasive resource in journalism, capable of shocking, frightening, or engaging audiences. Emotions are culturally inflected and thus frequently mediated through language; their strategic use in media discourse can shape reader involvement and understanding. The study’s functional-linguistic approach, focusing on emotive lexicon and its combinatorics, addresses gaps in representational and referential analyses by demonstrating how affective categories operate across modalities and syntactic/lexical structures. It underscores the importance of balancing emotional appeal with context and understanding in journalism to avoid intimidation and enhance audience engagement. Conceptual ambiguities among emotion-related terms persist, but the analysis shows practical ways emotive markers contribute to text construction and audience influence within digital, multimodal media environments.

The study mapped and analyzed emotive lexemes across parts of speech in Kazakh online media, demonstrating how multimodality, polyphony, hypertextuality, and heterogeneity contribute to meaning-making and audience influence. It identified and described emotive lexical units, examined layers of information constituting textual emotionality, and outlined pattern markers affecting textual variations. Results emphasize that digital media discourse requires both linguistic and extra-linguistic means to convey emotions, leveraging immediacy and spontaneity. The study’s insights can inform pedagogy in philology, psychology, journalism, and semiotics. Future research should examine integration of emotions’ linguistic and non-linguistic manifestations, particularly iconic emotive forms in Internet writing, to build a cognitive basis for studying iconic coding principles and associative memory mechanisms.

The study notes ambiguity in emotive items and difficulty determining how the emotional component of texts affects reader behavior.