Scientific Reports· 2026Q1
Modeling cross-media agenda interactions in the international communication of Chinese culture using multi-source news time-series data
- 0citations
- Q1SCImago
- 2026year
Short summary
A new time-series framework reveals structured predictive-precedence gradients in how Chinese culture is communicated across different media types, showing that network structure adds predictive power beyond issue salience alone.
AI-generated from the title and abstract; the full text is not read.
Key points
- Developed an integrated time-series framework combining agenda extraction, network representation, and advanced statistical modeling.
- Analyzed multi-source news data on Chinese culture's international communication (Jan 2021-Dec 2023).
- Identified structured predictive-precedence gradients across official, mainstream, and digital media outlets.
- Found that network structure indicators provide incremental predictive information beyond issue salience.
- Concluded that cross-media agenda evolution reflects structured temporal dependence and directed information association.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract Modeling cross-media agenda evolution is challenging because media agendas involve both temporal dependence in issue salience and structural reconfiguration among issue associations. Most existing intermedia agenda studies rely on contemporaneous correlations or simple lag comparisons, which reveal synchronization but provide limited evidence of predictive precedence across heterogeneous media systems. To address this limitation, this study develops an integrated time-series framework combining transformer-based agenda extraction, network agenda representation, cross-lag correlation analysis, vector autoregressive modeling, Granger-type predictive-dependence testing, and transfer entropy estimation. Using multi-source news time-series data on the international communication of Chinese culture from January 2021 to December 2023, we construct outlet-level measures of issue salience and structural agenda density and examine temporal-dependence patterns among official international media, global mainstream media, and digital-native or transnational online media. The results reveal structured predictive-precedence gradients across institutional media categories and hub-mediated agenda connectivity centered on selected intermediary outlets. Models incorporating structural indicators achieve higher explanatory power and lower forecast error than salience-only models, indicating that network configuration provides incremental predictive information beyond issue prominence alone. Overall, the findings suggest that cross-media agenda evolution reflects structured temporal dependence and directed information association rather than coincidental co-movement or definitive causal influence.
The authors' abstract, as published at the source. Scientific Reports, 2026 · DOI ↗
The rest is in the Pofolia app
Takeaways and questions to the paper; new summaries every day for your field. Free.
Sign in on the web to openField: Communication
CommunicationSocial Sciences