Effects of dehumanization and disgust-eliciting language on attitudes toward immigration: a sentiment analysis of Twitter data

Abstract

Attitudes towards immigration may be influenced by dehumanization and disgust: The more people dehumanize immigrants and the more disgusted they feel, the more negative their attitudes toward immigrants tend to be. Despite the fact that the majority of U.S. adults are on social media, however, little is known about how exposure to social media that links dehumanization, disgust and immigration influences users’ attitudes on this issue over time. We used Twitter data, machine learning and sentiment analysis to explore this question. Results showed that dehumanizing and/or disgust-eliciting language appeared in 66% of sampled immigration-relevant tweets. Surprisingly, exposure to both types of language in such tweets related to increases in positive sentiment about immigration over time. There was evidence of Granger-causality only for dehumanizing language, however, and only when controlling for communicators’ political affiliation. These findings suggest social media exposure may influence public attitudes toward immigration in unexpected ways.