Methods for the analysis of spreading phenomena in networks, with a focus on the online spreading of political ideas through visual content
Name: Matteo Magnani
Project title: Methods for the analysis of spreading phenomena in networks, with a focus on the online spreading of political ideas through visual content
Department: Information Technology
Area of research: Computational social science, data science, network analysis
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?
What do you look forward to the most during your sabbatical?
Having the time to set up this project, which has been developed together with Alexandra Segerberg (also a selected AI4Research researcher), identifying new areas where my research results can be applied, identifying new problems to solve, and also starting a broader cross-faculty initiative on the usage of AI methods in the social sciences.