The project Data-driven understanding of low-carbon lifestyles (LOW-AI) aims at using social media data to understand behavior change with respect to low-carbon lifestyles. In order to limit global warming to a safe level of 1.5℃, individual action is required. LOW-AI deploys social media data to monitor lifestyle changes and attitudes towards lifestyle changes in the global population, developing tools that can be implemented with a higher geographical reach and are less costly than traditional approaches.
The main objectives of LOW-AI consist of using social media data for quantifying the potential of feasible behavior change in the population and identifying the key drivers for a change that will lead to a decrease in carbon emission. This data allows to better understand people’s behavior with respect to climate change and could be used to inform existing models by extending climate change research to include the human behavioral component.
LOW-AI’s research is based on the use of social media data, which helps to gauge the interest of the public in topics related to climate change. The project will use this data to infer information about behavior change, and public attitudes towards it, that will complement already existing survey-based data both in terms of temporal and geographical coverage.
LOW-AI will first validate the use of social media data for the analysis of lifestyle choices of the general public against traditional data sources. In a second stage, the validated methods will be used to extend the available behavior information to countries, population groups and timeframes for which traditional data is missing. Finally, the results will be displayed in an interactive dashboard openly accessible to anyone.