Evidence map›Paper›PMID 37148448›Full record

ArticleJournal of psycholinguistic research2023

Association Strategies of Speech Behavior of Communicators in Coding Discourse: An Interdisciplinary Approach Towards Understanding the Role of Cognitive and Linguistic Processes in Communication.

Ludan Zhang, Irina Karabulatova, Artem Nurmukhametov, Margarita Lagutkina

RetractedAbstract readRetracted Publication
In one paragraph

Article in Journal of psycholinguistic research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ludan ZhangDepartment of Foreign Languages of Philological Faculty, Peoples Friendship University of Russia Named after Patrice Lumumba, RUDN University), Moscow, Russia.
Irina KarabulatovaDepartment of Foreign Languages of Philological Faculty, Peoples Friendship University of Russia Named after Patrice Lumumba, RUDN University), Moscow, Russia. radogost2000@mail.ru.
Artem NurmukhametovInstitute of Humanities, Yugra State University, Khanty-Mansiysk, Russia.
Margarita LagutkinaDepartment of Foreign Languages of Philological Faculty, Peoples Friendship University of Russia Named after Patrice Lumumba, RUDN University), Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In modern media, the names of fairy-tale and mythological images are used to convey certain emotions and connotations. The aim of the study is to analyze the characteristic associative strategies presented with the mythological images of a dragon, a paper tiger and a chimera in news texts of European and Chinese mass media. In this article, the method of text analysis was used to identify patterns and the most possible interpretations of lexical units. 100 articles from Chinese and European publications were selected for the analysis (About People's Daily Online, China News Service, Guardian and France 24). The required lexemes were most widely used in articles on political topics. The most used was the image of a paper tiger (4001 and 3587 units). This is due to its well-known metaphorical meaning in both cultures, while dragon differs in Chinese and European ones. Further research may focus on the search and analysis of other fairy tale and mythological images in mass media. The present study results may also be applied for further research in the field of linguistics and journalism.

Indexed as

CommunicationSpeechCognitionHumansLanguageLinguisticsAssociationsCultural imagesEmotive vocabularyFairy taleMythMythologeme

Identifiers

PMID37148448
PMCPMC10163285

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.