How Dehumanizing or Disgust-Eliciting Language in Tweets Shapes Views on Immigration

What is it about?

This study examined how social media posts containing dehumanizing or disgust-eliciting language about immigration may affect readers’ own views over time. Researchers used Twitter data and machine learning to see whether exposure to such negative language changes people’s sentiment about immigration. They tracked users’ tweet exposure and then measured sentiment shifts over time. Negative language online is common; 66% of tweets about immigration in the sample contained either dehumanizing or disgust-eliciting words. Surprisingly, exposure to these kinds of tweets was associated with small increases in positive sentiment toward immigration over time. Only dehumanizing language showed evidence of a causal influence when controlling for the political views of the people posting tweets. These findings suggest that online negativity might not always reinforce negativity among readers and may prompt unexpected or counter-intuitive effects on public attitudes.

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Photo by Claudio Schwarz on Unsplash

Photo by Claudio Schwarz on Unsplash

Why is it important?

Findings indicate that exposure to harsh language about immigration on social media may not always reinforce negative views. Instead, it may counterintuitively be linked to increases in positive sentiment over time. This challenges assumptions about how negativity spreads online. Understanding these dynamics can help inform more effective messaging strategies and interventions addressing immigration attitudes. It also offers new insight into how social media discourse shapes public perceptions in complex and surprising ways.