Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation

Yana Dudareva

doi:10.21603/vcsn-2026-5-2-138-150

UDC

81-139

CSCSTI

16.31

Russian Classification of Professions by Education

45.04.01

VAK Russia

5.9.9

IMPACT OF DERIVATIVE TEXT SENTIMENT ON SOURCE TEXT INTERPRETATION: INTERDISCURSIVE BUSINESS-TO-MEDIA TEXT DERIVATION Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation

АА Аа

Published in Virtual Communication and Social Networks · Pages 138–150 · Rubric: Media Communications and Journalism

DOI: https://doi.org/10.21603/vcsn-2026-5-2-138-150 · EDN: JCNMGJ

Received: 01.03.2026 Accepted: 30.03.2026 Published: 10.04.2026

Authors

Yana Dudareva

ORCID Scopus SPIN

Yana Dudareva

Kemerovo State University Russian Federation · Kemerovo

ORCID Scopus SPIN

ABSTRACT

As business texts enter media discourse, their derivational and variable-interpretive potential changes. Within the framework of official business discourse, business texts are standardized, clichéd, and neutral in sentiment. Media texts derived from business texts possess a specific communicative strategy that gives them elements of critical or approving tonality. This article describes the impact patterns of media (secondary / derivative) text sentiment and its communicative construction strategy on the interpretation of the source (primary / producing) business text. Using neural network sentiment analysis (DeepSeek), the authors identified media texts with a neutral sentiment, neutral sentiment with elements of latent critical tonality, and neutral sentiment with elements of positive (approving) sentiment. The intent analysis revealed the following communicative strategies for constructing media texts, combined with their sentiment: objective-critical presentation of facts; explanatory presentation of facts; selective presentation of facts (selective positive information); objective presentation of facts (complete information). An interpretive experiment, in which media texts were used as stimulus, revealed a number of correlations between the communicative strategies for constructing a media text, its sentiment, and the interpretation of the source business text. A neutral sentiment with positive (approving) elements, combined with an explanatory construction strategy, made the business text more comprehensible.

KEYWORDS

sentiment, communication strategies, text derivation, text adaptation, variable-interpretative functioning of text, neural network analysis, intent analysis, interpretive experiment

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This work is licensed under Creative Commons Attribution 4.0 International Creative Commons

GOST

Dudareva Y. A. Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation // . 2026. pp. 138-150. DOI: https://doi.org/10.21603/vcsn-2026-5-2-138-150. EDN: JCNMGJ. (Date of access 19.08.2026).

MLA

Yana Dudareva. "Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation." (2026): 138-150. DOI: https://doi.org/10.21603/vcsn-2026-5-2-138-150. EDN: JCNMGJ.

APA

Dudareva Y. A. (2026). Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation. , 138-150. https://doi.org/10.21603/vcsn-2026-5-2-138-150 EDN: JCNMGJ.

Chicago

Yana Dudareva. "Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation." , no. (2026): 138-150. https://doi.org/10.21603/vcsn-2026-5-2-138-150. EDN: JCNMGJ.

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{{cite journal | author = Dudareva Y. A. | title = Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation | journal = | year = 2026 | pages = 138-150 | doi = 10.21603/vcsn-2026-5-2-138-150 }} EDN: JCNMGJ

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IMPACT OF DERIVATIVE TEXT SENTIMENT ON SOURCE TEXT INTERPRETATION: INTERDISCURSIVE BUSINESS-TO-MEDIA TEXT DERIVATION Impact of Derivative Text Sentiment on Source Text Interpretation: Interdiscursive Business-to-Media Text Derivation

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