Predicting the performance of Facebook advertisements about climate change using self-report data

Social media has become an important medium for climate change communication, where sponsored content can be delivered to specific audiences. However, studying message effects on social media platforms has limitations and therefore scholars often rely on surveys and controlled experiments, which can lack external validity. Here, we use survey methods to predict the real-world performance of advertisements on Facebook. We found that a 10 percentage point increase in self-reported likelihood of sharing a post predicted 55% more actual shares, and a 10 percentage point increase in perceptions that the post would be interesting to others predicted 86% more shares. We also found a U-shaped relationship between people’s emotional reactions to the posts and the number of shares, such that emotionally-neutral posts were shared less often than posts that elicited either a strongly positive or negative emotional response. We then discuss the strategic and practical applications of these findings.