Abstract Book of the 18th International Conference on Humanities, Psychology and Social Sciences
Year: 2025
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From Policy To Perception: Media Sentiment in The Wake of Immigration Policies
Nicholas Revenco, Munveer Singh, and Zach Tan
ABSTRACT:
Despite extensive research on agenda-setting theory—which demonstrates how media shapes public perception and influences policy formation—there remains a gap in understanding how immigration policy changes influence media sentiment toward immigrants. Our study addresses this limitation by analyzing 23,164 immigration-related news articles from 189 media sources before and after five major U.S. immigration policies (2017-2021): Trump Travel Ban, TPS Termination, Public Charge Rule, Title 42, and DACA Reinstatement. Using LLM-based sentiment analysis with a detailed codebook (intercoder reliability α=0.816), we evaluated sentiment changes across left, moderate, and right-leaning sources.
Paired-sample tests reveal sharp ideological responses: left-leaning coverage turned significantly positive after DACA reinstatement (+0.28, p=.006); the 2018 TPS rollback drove negativity across the political spectrum (left=-0.32, right=-0.18, both p<.05). Moderate sources showed a notably large shift, suggesting decreasing media neutrality. Sentiment changes correlate significantly with outlet political bias during DACA (r=-.43, p=.047), providing empirical support for a cyclic feedback loop between government policies and media sentiment.
These findings challenge traditional linear agenda-setting models and demonstrate that policy changes directly influence media narratives. The research reveals how immigration policies may create a feedback loop where policy changes increase media polarization, potentially influencing future public opinion and policy-making cycles.
Keywords: Agenda-setting, Immigration policy, Media framing, Media bias, Sentiment analysis