Assessing GDELT with handcoded protest data

For my dissertation, I’ve been working on a way to generate new protest event data using principles from natural language processing and machine learning. In the process, I’ve been assessing other datasets to see how well they have captured protest events. I’ve mused on before on assessing GDELT (currently under reorganized management) for protest events. One of the… Continue reading →