Unveiling user dynamics in the evolving social debate on climate crisis during the conferences of the parties

Abstract

Social media have widely been recognized as a valuable proxy for investigating users’ opinions by echoing virtual venues where individuals engage in daily discussions on a wide range of topics. Among them, climate change is gaining momentum due to its large-scale impact, tangible consequences for society, and enduring nature. In this work, we investigate the social debate surrounding climate emergency, aiming to uncover the fundamental patterns that underlie the climate debate, thus providing valuable support for strategic and operational decision-making. To this purpose, we leverage Graph Mining and NLP techniques to analyze a large corpus of tweets spanning seven years pertaining to the Conference of the Parties (COP), the leading global forum for multilateral discussion on climate-related matters, based on our proposed framework, named NATMAC, which consists of three main modules designed to perform network analysis, topic modeling and affective computing tasks. Our contribution in this work is manifold: (i) we provide insights into the key social actors involved in the climate debate and their relationships, (ii) we unveil the main topics discussed during COPs within the social landscape, (iii) we assess the evolution of users’ sentiment and emotions across time, and (iv) we identify users’ communities based on multiple dimensions. Furthermore, our proposed approach exhibits the potential to scale up to other emergency issues, highlighting its versatility and potential for broader use in analyzing and understanding the increasingly debated emergent phenomena.