Celebration of Scholarship and Creative Activity 2023
A Computational Text Analysis of Congress’s Immigration Discourse on Twitter
Yanet Fernandez
Senior, Mathematics-Statistics Emphasis
Abstract
Immigration has been a topic of discussion for decades, especially with the increasing number of immigrants from Latin America and the media highlighting politicians’ polarized opinions on immigration-directed policies. To better understand the discourse of immigration among political leaders, a computational text analysis was used to study over 1.5 million tweets sent from members of the 115th and 116th House of Representatives, from 2017 to 2020. This study examines how the discourse is shaped by district characteristics such as the share of foreign-born population and partisan representation. To convey differences in district composition and possible geographical trends of the conversations, congressional district maps were generated to provide context and visualize tweeting activity on a scale of congressional districts. A temporal analysis showcased significant changes in the discourse corresponding to key events which may indicate challenges and societal shifts in perspective regarding immigration. There were differences in the frequency of Twitter activity pertaining to immigration issues relative to partisanship. Finally, a TF-IDF was conducted and disclosed that unique word usage regarding immigration among each party was evident. Studying the conversations of immigration using computational text analysis can aid in comprehending immigration politics, political behavior, and how opinions are conveyed.
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