Combining remote sensing and social media data to predict indicators of political and economic instability

John M. Irvine; Brigid Angelini; Admir Monteiro; Max Turnquist; Michael Crystal

doi:10.1117/12.2664151

18 July 2023 Combining remote sensing and social media data to predict indicators of political and economic instability

John M. Irvine, Brigid Angelini, Admir Monteiro, Max Turnquist, Michael Crystal

Proceedings Volume 12525, Geospatial Informatics XIII ; 1252504 (2023) https://doi.org/10.1117/12.2664151
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Understanding a region’s socio-economic conditions can inform the development of policies in both the public and private sectors. Commercial satellite imagery provides socio-economic context. By combining commercial imagery with geospatially enhanced social media, we generate local measures of political and economic instability risks at a regional and national scale. We present models that generate instability estimates by fusing socio-economic contextual data from commercial imagery with high-tempo social media data. To assess model performance, we predict annual indicators of conditions for a country as assessed by the World Bank. The models relate model-derived features to indicators of political stability, control of corruption, rule of law, government effectiveness, voice and accountability, and gross domestic product using data from multiple countries. Comparison of our methods to the World Bank data demonstrate the strengths of our approach.

Conference Presentation

Citation Download Citation

John M. Irvine, Brigid Angelini, Admir Monteiro, Max Turnquist, and Michael Crystal "Combining remote sensing and social media data to predict indicators of political and economic instability", Proc. SPIE 12525, Geospatial Informatics XIII , 1252504 (18 July 2023); https://doi.org/10.1117/12.2664151

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