Evidence map›Paper›PMID 42103906›Full record

ArticleScientific reports2026

Asymmetric effects of semantic compatibility and structural bridging on content propagation: evidence from community vernacular combinations on social media platforms.

Jingjing Mu, Xing Yuan, Vasylieva Olena Serhiivna, Qian Zhao, Yue Zhu

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jingjing MuSchool of Art and design, Communication University of China, Nanjing, 211172, Jiangsu Province, China.
Xing YuanSchool of Art & Design, Shaanxi University of Science & Technology, Xian, 710021, Shaanxi Province, China. XingYuanUkraine@outlook.com.
Vasylieva Olena SerhiivnaDepartment of Multimedia Design, Kyiv National University of Technologies and Design, Kyiv, Ukraine.
Qian ZhaoSchool of Art and design, Communication University of China, Nanjing, 211172, Jiangsu Province, China.
Yue ZhuSchool of Art & Design, Shaanxi University of Science & Technology, Xian, 710021, Shaanxi Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid expansion of social media platforms and the fragmentation of interest communities have created new theoretical demands for understanding content propagation. Users routinely combine community-specific semantic vernaculars in their content, yet combination-level propagation patterns remain invisible within single-vernacular frameworks. This study constructs a color vernacular co-occurrence network from ACG-related posts on Xiaohongshu (January 2024 to March 2025) and examines how cognitive hierarchy compatibility and network structural position jointly associate with combination propagation outcomes. Three findings emerge. First, semantic hierarchy compatibility positively associates with propagation synergy: within-level compatible combinations correspond to higher propagation gains and cross-level incompatible combinations correspond to negative synergy. Second, cognitive distance associates with propagation outcomes in a monotonically accelerating declining pattern, which does not support the inverted-U hypothesis, because the cognitive gains from semantic novelty cannot offset the decoding burden that accelerates as hierarchical distance increases. Third, semantic hierarchy and community structure show opposite directional associations: cross-level semantics correspond to a negative association while cross-community bridging corresponds to a positive association, and cognitively compatible cross-community combinations consistently outperform incompatible ones. Maintaining semantic hierarchy compatibility while pursuing structural bridging, and incorporating cognitive compatibility into platform recommendation mechanisms, are productive directions for future research.

Indexed as

Information DisseminationSemanticsSocial MediaHumansCommunity vernacularPlatform propagation mechanismSemantic compatibilitySocial network analysisStructural bridging

Identifiers

PMID42103906
PMCPMC13346501

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LicenceCC BY
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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.