Session | ||
OS-194: Social Networks and Climate Change 3
Session Topics: Social Networks and Climate Change
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Presentations | ||
A Longitudinal Analysis of Climate Change Discourse Coalitions over 28 years of United Nations COP Meetings University of British Columbia, Canada This paper examines how discourse coalitions and conflicts of nation-states at UN COP conferences have changed over time, and consider how this relates to changes in global political economy. My dataset consists of over 2,300 speeches by nation-state representatives from COP1 in 1995 to COP28 in 2023, compiled from United Nations archives and national government websites. In these speeches, representatives highlight important issues they see as relevant to climate change, their recent and planned climate-related actions, and the COP process and their participation in it. I use topic modelling to identify distinct climate-related topics, and groups of nation-states adhering to these topics at different times. I analyze points of convergence and conflict throughout nearly three decades of the UNFCCC process, and consider how these relate to changes within countries and across the global political economy, with particular focus on comparing how the discourses of developed, developing, and BRICs countries change over time. How Sources and Framing Strategies Shape Network Dynamics in Climate Skepticism Discourse: An Exponential Random Graph Model Approach Pukyong National University, Korea, Republic of (South Korea) Misinformation, disinformation, and fake news about climate change are widespread on social media. Climate skepticism can be contagious as climate change is not just an environmental issue but also intertwined with social, political, and economic concerns. Alerting messages from climate change deniers, labeling it a “climate scam,” have fueled conversations on social media. However, the mechanisms driving social connectivity and information dissemination in climate skepticism discourse remain understudied. This study addresses this gap by examining how source characteristics and message framing strategies shape user interactions in the climate skepticism network, employing a mixed-method approach that integrates an Exponential Random Graph Model (ERGM) and content analysis. The model includes source attributes, distinguishing between individual and organizational accounts and classifying individuals as celebrities or non-celebrities. Dominant framing strategies in skeptical conversations are included as edge attributes. The homophily effect is tested to assess the likelihood of conversational tie formation between similar sources, while clustering effects are analyzed to determine whether specific sources and framing strategies drive network cohesion. X network data on “climate scam” from January 1 to March 1, 2024, was collected and analyzed. The unit of analysis consists of 19,872 unique users and 53,103 conversational ties, forming a directed network. Preliminary findings indicate that the network exhibits a small-world structure with high clustering. The dominant framing strategies are conspiratorial, political, and scientific. This study enhances understanding of the generative processes behind opinion formation and echo chamber effects in climate skepticism, shedding light on their potential role in climate policy opposition. Interpretable Early Warnings using Machine Learning in an Online Game-experiment Princeton University The solutions to environmental crises are known, but social dilemmas illustrate what stands in the way of implementing them : actors free-ride on ecosystem health benefits, even those who deteriorate these ecosystems. Mechanisms to reduce defection in social dilemmas have been proposed, but are often limited to small groups - whereas socio-environmental crises require global systemic cooperation. I propose the CORESO/COOLNET project to discover, using video games, what structures of social interactions at all scales can foster such cooperation. To this end, we will build a common formalism for the driving mechanisms of cooperation already proposed, as well as for new ones that we will explore. Large-scale processes are difficult to study in a traditional laboratory, or in-situ without experimental control. We will develop an massively multiplayer online game as an experimental platform for large-scale cooperation. This will allow to test, in particular, the effect of emergent phenomena such as positive social tipping points and of multi-layer network structures on global cooperation. Depending on our results, we could transfer these results to public policy recommendations, in the form of cheap top-down interventions favoring bottom-up emergence. We will also adapt the game into a local governance workshop to guide collective decision-making. |