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In the last decade, international relations scholarship on shaming by NGOs has grown dramatically, providing us with many insights on how country-level improvement occurs in the area of human rights and the environment, among other issues. Using machine learning techniques, this project builds a new and updated dataset on NGO shaming. Our approach allows for researchers to explicitly examine shaming as a dyadic or network event, occurring from a specific sender to a specific target. Using our new dataset, we first validate existing research on shaming in the current populist era and then test novel hypotheses on how the nature of the NGO and the nature of the country interact to facilitate shaming in certain instances. Our approach and dataset will be useful both to academics and to the policy community.
Robert Thuan Brathwaite, Michigan State University
Shanshan Lian
Amanda Murdie, University of Georgia
Baekkwan Park