ALMONDO is a PRIN PNRR project funded by the Italian Government (MIUR) N. P2022N2TPJ

In this project, we propose a novel modeling framework to study climate lobbying that carefully considers the features of human learning and communication, is grounded on empirical observations, allows for scenario analysis, improves policy design, and is embedded in a ready-to-use and user-friendly computational tool.

Fostering consensus on climate change consequences is crucial for sustainable development. Hence, understanding how climate-related opinions dynamically change and which are the best strategies to spread climate-related scientific information in our complex and interconnected society becomes crucial.

Blending knowledge from economics and computer science, our modeling approach incorporates opinion dynamics models with explicit consideration of behavioral biases for a realistic perspective.

Our modeling approach starts with opinion dynamics models, modified to explicitly include behavioral biases in climate-related interactions for a more realistic perspective.

To address challenges in linking models and data, we employ systematic data mining, econometric studies, and laboratory experiments. Our data collection spans various climate lobbying actors, from policymakers to citizens. Advanced econometric and data science techniques are applied for thorough analysis.

Once calibrated, our model will shed light on lobbying dynamics and opinions, offering recommendations through a user-friendly website offering recommendations for environmental consensus and sustainable development.