Socioeconomic Prediction
Socioeconomic prediction aims to forecast indicators of societal well-being using diverse data sources, primarily to inform policy and improve resource allocation. Current research heavily utilizes machine learning, particularly deep learning models like encoder-decoder architectures and contrastive learning frameworks, often incorporating multi-modal data (satellite imagery, street view images, mobile app usage, and text data) to improve prediction accuracy and interpretability. These advancements offer the potential for more precise and timely monitoring of sustainable development goals and improved understanding of socioeconomic disparities, enabling more effective interventions in areas like poverty reduction and urban planning.
Papers
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