Food and water insecurity as causes of social unrest: Evidence from geolocated Twitter data

Research often fails to account for the specific pathways by which climatic factors can cause social unrest. One challenge lies in understanding the distinct effects of food insecurity and water insecurity – which we term ‘staple insecurities’ – while accounting for their interrelated nature, especially at high-resolution spatio-temporal scales. To unpack these dynamics, we leverage geolocated Twitter data across urban areas in Kenya and deploy a supervised machine learning approach to separately identify geolocated tweets concerning food and water insecurity, in both English and Swahili. The data are then aggregated to create daily measures of food and water insecurity for standardized grid-cells to examine how perceived food insecurity moderates and/or reinforces perceived water insecurity’s impacts on social unrest, and vice versa. Our findings suggest that food and water insecurities’ respective effects should be interpreted as mutually reinforcing – in compelling citizens to take to the streets – rather than as independent. Those concerned with climate change’s impact on conflict should hence endeavor to jointly account for both forms of insecurity, and their interactive effects.