Wednesday, August 3, 2022
Data scientists have used computational analysis (aka machine learning) to comb through 150 years of political speeches and find that attitudes toward immigrants are more positive, but also more partisan.
The study, co-authored by Dallas Card and colleagues from Stanford University, charts the tone of more than 200,000 congressional and presidential speeches on immigration since 1880. Published in Proceedings of the National Academy of Sciences, the study finds that the overall trend of political speeches became more sympathetic following World War II and has remained favorable, on average, until today.
At the same time, however, attitudes have become increasingly polarized along party lines. Democratic rhetoric has been reliably sympathetic toward immigrants since the 1960s, and especially pro-immigration in the past decade, while that of Republicans has become increasingly hostile since the 1990s, and more likely to characterize immigrants with subtle de-humanizing language.