2022
By Christel van Eck, Anne Kroon, and Damian Trilling
While increasingly more studies focus on online climate change polarization dynamics, research on ‘processes’ of polarization (instead of ‘states’ of polarization) and research on depolarization dynamics is largely overlooked. Hence, the current study investigates online climate change polarization and depolarization dynamics, by analyzing Dutch comment interactions about climate change on Youtube and Twitter. A sample of comments is manually annotated by crowd coders based on the following concepts: (a) users’ global warming stance; (b) escalation; and (c) identity labeling. Using these annotations, we train a BERT supervised classifier to predict class membership in a large-scale dataset of social media comments on the topic of climate change. This project provides insight into how climate change polarization emerges, accelerates, and dissolves online.