Analysis of Climate Campaigns on Facebook using Weakly Supervised Model Soup Approach

Anonymous

Abstract: Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective action on this issue on social media. In addition, issue advocacy campaigns in social media often arise in response to ongoing societal concerns, especially those faced by energy industries. Our goal in this paper is to analyze how those industries, their advocacy group, and climate advocacy group use social media to influence the narrative on climate change. In this work, we propose a weakly supervised model soup approach combined with messaging themes to identify the stances of climate ads on Facebook. Finally, we release our stance dataset, model, and set of themes related to climate campaigns for future work on opinion mining and the automatic detection of climate change stances. Our data, code, and model are anonymously available here.

Paper Type: long

Research Area: Computational Social Science and Cultural Analytics