Selling the Smart Border: A Comparative NLP Analysis Of U.S. Immigration Technology Narratives Under Trump and Biden

Republicans and Democrats often claim to have extremely polarizing policies and values, especially regarding immigration and the U.S.-Mexico border. This study examines whether their immigration narratives and use of technology are truly as different as they seem. This paper looks at how immigrant narratives and techno-optimism (the belief that technology can solve major social problems) shaped immigration policies under the Trump (1st term) and Biden administrations. Using natural language processing (NLP) methods, including topic modeling and sentiment analysis, it analyzes presidential documents to understand how each administration talks about immigrants and uses technology in immigration enforcement. The results show that while there are some differences, there are also important similarities, particularly in how both administrations use technology in ways that may still exclude or harm immigrants. By comparing the two administrations, this study questions the idea that partisan divides always lead to completely different immigration policies.