Affective Polarization in Online Climate Change Discourse on Twitter

TL;DR

This paper introduces a network-based method to quantify affective polarization in online climate change discussions on Twitter, revealing that climate change skeptics are more hostile and use more disaster-related language during hostile periods.

Contribution

It develops a systematic framework for measuring affective polarization in online discourse and applies it to a large Twitter dataset about climate change, providing new insights into online hostility.

Findings

Disbelievers are more hostile towards Believers than vice versa.

Disbelievers use more disaster-related words during hostile weeks.

Hostility correlates with increased natural disaster language.

Abstract

Online social media has become an important platform to organize around different socio-cultural and political topics. An extensive scholarship has discussed how people are divided into echo-chamber-like groups. However, there is a lack of work related to quantifying hostile communication or \textit{affective polarization} between two competing groups. This paper proposes a systematic, network-based methodology for examining affective polarization in online conversations. Further, we apply our framework to 100 weeks of Twitter discourse about climate change. We find that deniers of climate change (Disbelievers) are more hostile towards people who believe (Believers) in the anthropogenic cause of climate change than vice versa. Moreover, Disbelievers use more words and hashtags related to natural disasters during more hostile weeks as compared to Believers. These findings bear implications for studying affective polarization in online discourse, especially concerning the subject of climate change. Lastly, we discuss our findings in the context of increasingly important climate change communication research.