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

09/10/2021
by   Totte Harinen, et al.
0

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 some people's belief in climate change while resulting in decreased belief in others. In particular, we show that the effect of the advertisements could change depending on people's age and ethnicity.

READ FULL TEXT
research
07/07/2021

Climate Change Conspiracy Theories on Social Media

One of the critical emerging challenges in climate change communication ...
research
08/06/2023

The Facebook Algorithm's Active Role in Climate Advertisement Delivery

Communication strongly influences attitudes on climate change. Within sp...
research
12/17/2021

Free-Riding for Future: Field Experimental Evidence of Strategic Substitutability in Climate Protest

We test the hypothesis that protest participation decisions in an adult ...
research
06/18/2013

Bioclimating Modelling: A Machine Learning Perspective

Many machine learning (ML) approaches are widely used to generate biocli...
research
11/26/2019

A User Study of Perceived Carbon Footprint

We propose a statistical model to understand people's perception of thei...
research
11/06/2022

Personalizing Sustainable Agriculture with Causal Machine Learning

To fight climate change and accommodate the increasing population, globa...
research
04/15/2015

Bridging belief function theory to modern machine learning

Machine learning is a quickly evolving field which now looks really diff...

Please sign up or login with your details

Forgot password? Click here to reset