People can understand IPCC visuals and are not influenced by colors
Bibliographic Data
| ID | 15549273 |
|---|---|
| Authors | Vittoria Battocletti (0000-0003-0726-2487, Bocconi University), Alessandro Romano (0000-0002-2041-5487, Bocconi University), Chiara Sotis (0000-0001-9367-0932, London School of Economics and Political Science, corresponding author) |
| Year | 2023 |
| Volume | 18 |
| Issue | 11 |
| Pages | 114036-114036 |
| Publication date | 2023-09-20 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/acfb95 |
| OpenAlex | W4386881180 |
| Language | EN |
| Citations received | 1 |
| References cited | 37 |
We carry out two online experiments with large representative samples of the US population to study key climate visuals included in the Sixth Report of the Intergovernmental Panel on Climate Change (IPCC). In the first study ( N = 977), we test whether people can understand such visuals, and we investigate whether color consistency within and across visuals influences respondents’ understanding, their attitudes toward climate change and their policy preferences. Our findings reveal that respondents exhibit a remarkably good understanding of the IPCC visuals. Given that IPCC visuals convey complex multi-layered information, our results suggest that the clarity of the visuals is extremely high. Moreover, we observe that altering color consistency has limited impact on the full sample of respondents, but affects the understanding and the policy preferences of respondents who identify as Republicans. In the second study ( n = 1169), we analyze the role played by colors’ semantic discriminability, that is the degree to which observers can infer a unique mapping between the color and a concept (for instance red and warmth have high semantic discriminability). We observe that semantic discriminability does not affect attitudes toward climate change or policy preferences and that increasing semantic discriminability does not improve understanding of the climate visual
Affect (linguistics · CLARITY · Climate change · Cognitive psychology · Consistency (knowledge bases · Population · Sociology · Animal and Plant Science Education · Climate Change Communication and Perception · Computer Science · Psychology · Artificial Intelligence · Communication · Ecology
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |