Abstract

In the present study we set out to examine an audience segmentation system that can be used to inform global warming public engagement campaigns and to test survey-based identification tools designed by the Yale Project on Climate Change Communication. A national poll was conducted in Spain with a representative sample of the population online (n = 602). The survey included measures concerning pro-environmental behavior and intentions, issue involvement, individuals’ beliefs, and preferred societal response. The population was classified with reference to their level of concern. Our results show four distinct interpretive communities, ranging from alarmist to dismissive. Overall, the largest audience segment was the concerned, who are convinced that global warming is happening but not engaged personally. The sample was classified using two-step cluster analysis, as we have a really large data set, which does clustering algorithms based on a distance measure. The relationships between the items were also examined in order to identify the possible correlations and recognize how behavior is affected by intentions, beliefs, preferred societal response, and issue involvement.