Global Warming’s Six MTurks: A Secondary Analysis of a US-Based Online Crowdsourcing Market
|Title||Global Warming’s Six MTurks: A Secondary Analysis of a US-Based Online Crowdsourcing Market|
|Year of Publication||2022|
|Authors||Austhof, E, Brown, H|
|Journal||International Journal of Environmental Research and Public Health|
|Keywords||audience segmentation, climate change, global warming, health communication, public health, risk perception|
Using a global warming audience segmentation tool (Six Americas Super Short Survey (SASSY)) as a case study, we consider how public health can use consumer panels and online crowdsourcing markets (OCMs) in research. Through a secondary analysis, we aim to understand how consumer panels and OCMs are similar to or different from each other on demographics and global warming beliefs through SASSY, and how they compare to US Census estimates. With this information, researchers will understand public opinion of global warming in their sample, which is useful for many climate change initiatives. Neither the consumer panel (Ipsos) or OCM sample (MTurk) matched US estimates of population demographics. Both panels achieved similar SASSY segments, showing that even with diverse sampling frames, SASSY is a useful tool for understanding global warming sentiment. Compared to Ipsos, MTurk was younger (more Millennials and Generation X), had higher educational attainment, and lower income. Both panels were majority White, but Ipsos was more diverse than the unweighted MTurk. Ipsos had more respondents from the South whereas MTurk had more respondents from the West. Across the MTurk SASSY segment, there were no significant differences for the majority of demographic characteristics except for age; younger generations were more Alarmed or Concerned, and older generations were more Doubtful and Dismissive. Researchers interested in understanding their sample’s opinions of global warming should use SASSY and consider oversampling in key demographic variables if they intend to achieve a nationally representative and diverse sample.