Cross-Modal Emotion Propagation and Risk Warning Modeling Based on Multi-Source Remote Sensing Data: A Case Study of Social Media During the Epidemic
DOI:
https://doi.org/10.53469/wjimt.2025.08(08).02Keywords:
Cross-modal analysis, Emotion propagation, Epidemic warning, Social media, Remote sensing dataAbstract
To describe the spatiotemporal propagation paths of public emotions during major public health emergencies, this study builds a cross-modal risk analysis framework that integrates remote sensing heatmaps, social media text, and epidemic data. A BERT-based text sentiment model and a CNN-LSTM multimodal embedding method are used, combined with graph convolutional networks to capture regional diffusion effects. Using the early 2020 epidemic as a case, the model successfully identified several high-incidence areas of social panic up to two weeks in advance. The results show significant value for precise government intervention and resource allocation.
References
Xiao, Y., Tan, L., & Liu, J. (2025). Application of Machine Learning Model in Fraud Identification: A Comparative Study of CatBoost, XGBoost and LightGBM.
Gong, C., Zhang, X., Lin, Y., Lu, H., Su, P. C., & Zhang, J. (2025). Federated Learning for Heterogeneous Data Integration and Privacy Protection.
Zhong, Z., Wang, B., & Qi, Z. (2025). A Financial Multimodal Sentiment Analysis Model Based on Federated Learning.
Xie, W., Zhao, X., & Chen, H. (2025). Intelligent Fitness Data Analysis and training Effect Prediction Based on Machine Learning Algorithms.
Liu, J., Huang, T., Xiong, H., Huang, J., Zhou, J., Jiang, H., ... & Dou, D. (2020). Analysis of collective response reveals that covid-19-related activities start from the end of 2019 in mainland china. medRxiv, 2020-10.
Tian, J., Lu, J., Wang, M., Li, H., & Xu, H. (2025). Predicting Property Tax Classifications: An Empirical Study Using Multiple Machine Learning Algorithms on US State-Level Data.
Wang, Y., Han, X., & Zhang, X. (2025). AI-Driven Market Segmentation and Multi-Behavioral Sequential Recommendation for Personalized E-Commerce Marketing.
Yuan, T., Zhang, X., & Chen, X. (2025). Machine Learning based Enterprise Financial Audit Framework and High Risk Identification. arXiv preprint arXiv:2507.06266.
Zhang, Z., Li, Y., Huang, H., Lin, M., & Yi, L. (2024, September). Freemotion: Mocap-free human motion synthesis with multimodal large language models. In European Conference on Computer Vision (pp. 403-421). Cham: Springer Nature Switzerland.
Yang, J. (2025). Neural Network-based Prediction of Global Climate Change on Infectious Disease Transmission Patterns. International Journal of High Speed Electronics and Systems, 2540584.
Zhang, F. (2025). Distributed Cloud Computing Infrastructure Management. International Journal of Internet and Distributed Systems, 7(3), 35-60.
Qiu, Y. (2024). Financial Deepening and Economic Growth in Select Emerging Markets with Currency Board Systems: Theory and Evidence. arXiv preprint arXiv:2406.00472.
Chen, H., Li, J., Ma, X., & Mao, Y. (2025). Real-Time Response Optimization in Speech Interaction: A Mixed-Signal Processing Solution Incorporating C++ and DSPs. Available at SSRN 5343716.
Liang, R., Ye, Z., Liang, Y., & Li, S. (2025). Deep Learning-Based Player Behavior Modeling and Game Interaction System Optimization Research.
Qiu, Y., & Wang, J. (2022). Credit Default Prediction Using Time Series-Based Machine Learning Models. In Artificial Intelligence and Applications.
Zhan, S., Lin, Y., Zhu, J., & Yao, Y. (2025). Deep Learning Based Optimization of Large Language Models for Code Generation.
Gui, H., Fu, Y., Wang, Z., & Zong, W. (2025, April). Research on Dynamic Balance Control of Ct Gantry Based on Multi-Body Dynamics Algorithm. In 2025 6th International Conference on Mechatronics Technology and Intelligent Manufacturing (ICMTIM) (pp. 138-141). IEEE.
Zhang, Z., Ding, J., Jiang, L., Dai, D., & Xia, G. (2024). Freepoint: Unsupervised point cloud instance segmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 28254-28263).
Gui, H., Wang, B., Lu, Y., & Fu, Y. (2025). Computational Modeling-Based Estimation of Residual Stress and Fatigue Life of Medical Welded Structures.
Zhan, S., & Qiu, Y. (2025). Efficient Big Data Processing and Recommendation System Development with Apache Spark. benefits, 4, 6.
Yang, J. (2023, March). Research on the propagation model of COVID-19 based on virus dynamics. In Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022) (Vol. 12611, pp. 962-967). SPIE.
Chen, F., Liang, H., Yue, L., Xu, P., & Li, S. (2025). Low-Power Acceleration Architecture Design of Domestic Smart Chips for AI Loads.
Liang, R., Feifan, F. N. U., Liang, Y., & Ye, Z. (2025). Emotion-Aware Interface Adaptation in Mobile Applications Based on Color Psychology and Multimodal User State Recognition. Frontiers in Artificial Intelligence Research, 2(1), 51-57.
Yang, M., Wu, J., Tong, L., & Shi, J. (2025). Design of Advertisement Creative Optimization and Performance Enhancement System Based on Multimodal Deep Learning.
Yang, M., Cao, Q., Tong, L., & Shi, J. (2025, April). Reinforcement learning-based optimization strategy for online advertising budget allocation. In 2025 4th International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID) (pp. 115-118). IEEE.
Peng, H., Jin, X., Huang, Q., & Liu, S. (2025). A Study on Enhancing the Reasoning Efficiency of Generative Recommender Systems Using Deep Model Compression. Available at SSRN 5321642.
Zheng, J., & Makar, M. (2022). Causally motivated multi-shortcut identification and removal. Advances in Neural Information Processing Systems, 35, 12800-12812.
Xu, K., Mo, X., Xu, X., & Wu, H. (2022). Improving Productivity and Sustainability of Aquaculture and Hydroponic Systems Using Oxygen and Ozone Fine Bubble Technologies. Innovations in Applied Engineering and Technology, 1-8.
Yao, Y. (2022). A review of the comprehensive application of big data, artificial intelligence, and internet of things technologies in smart cities. Journal of computational methods in engineering applications, 1-10.
Zhan, S., Lin, Y., Yao, Y., & Zhu, J. (2025, April). Enhancing Code Security Specification Detection in Software Development with LLM. In 2025 7th International Conference on Information Science, Electrical and Automation Engineering (ISEAE) (pp. 1079-1083). IEEE.
Fu, Y., Gui, H., Li, W., & Wang, Z. (2020, August). Virtual Material Modeling and Vibration Reduction Design of Electron Beam Imaging System. In 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA) (pp. 1063-1070). IEEE.
Lin, Y., Yao, Y., Zhu, J., & He, C. (2025, March). Application of Generative AI in Predictive Analysis of Urban Energy Distribution and Traffic Congestion in Smart Cities. In 2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE) (pp. 765-768). IEEE.