Images are a powerful means of sharing information and have been shown to increase the probability of information spreading and user engagement. In particular, images can be used to spread political messages (for example, for or against climate change mitigating actions), contributing to the definition of the public agenda. Current methods to study political communication through visual content rely on the manual inspection of selected pictures by domain experts, often in print news media. This is an approach that cannot scale to the complex contemporary communicative ecology made of multiple interconnected social and traditional media. This project will address the following research questions: How can we use AI methods rooted in network analysis to extend our ability to map and interpret online visual narratives in depth, at scale and across multiple social networks? What visual narratives around climate change exist and how can they be characterised with respect to their visibility, engagement, polarisation, and temporal evolution?