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Poster
in
Workshop: Causal Machine Learning for Real-World Impact

Machine learning reveals how personalized climate communication can both succeed and backfire

Totte Harinen · Alexandre Filipowicz · Shabnam Hakimi · Rumen Iliev · Matt Klenk · Emily Sumner


Abstract:

Different advertising messages work for different people. Machine learning can be an effective way to personalise climate communications. In this paper, we use machine learning to reanalyse findings from a recent study, showing that online advertisements increased climate change belief in some people while resulting in decreased belief in others. In particular, we show that the effect of the advertisements could change depending on a person's age and ethnicity. Our findings have broad methodological and practical applications.

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