What question did this study set out to answer?

This research aims to develop a new evaluation framework to measure news communication influence using a multimodal approach.

July 10, 2026Discover Artificial IntelligenceOpen Access

A comprehensive evaluation system for news communication influence based on multimodal graph neural network

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Authors

XZX ZhaoChongqing University of Posts and Telecommunications XGXiaoliang GongDNV (Norway)

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Implication

Randomized trial demonstrates enhanced classification accuracy of news communication influence using multimodal graph neural network, suggesting a new evaluation framework.

Key Points

This research aims to develop a new evaluation framework to measure news communication influence using a multimodal approach.
Utilized the Scalable Locust Swarm Optimized Multimodal Graph Neural Network (SLS-MGNN) framework.
Preprocessed multimodal data including text, images, audio, and video from the Chinese News Communication Influence Dataset.
Employed feature extraction techniques such as Bag-of-Words for text and CNNs for visual content.
Achieved 99% accuracy and F1-score in multi-class classification of public opinion trends.
Outperformed baseline models like SVM, Decision Tree, and Random Forest in terms of classification performance.
Provided interpretable insights into cognitive, emotional, and behavioral influence patterns.

Cite This Study

Zhao et al. (2026) studied this question.

synapsesocial.com/papers/6a508e5b6eeac72a437a139d https://doi.org/10.1007/s44163-026-01477-9

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Implication

Randomized trial demonstrates enhanced classification accuracy of news communication influence using multimodal graph neural network, suggesting a new evaluation framework.

A comprehensive evaluation system for news communication influence based on multimodal graph neural network

Discussion

Member takes

Implication

Key Points

Cite This Study

A comprehensive evaluation system for news communication influence based on multimodal graph neural network

Discussion

Member takes

Implication

Key Points

Cite This Study

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