Debnath Ramit, Ebanks Danny, Mohaddes Kamiar, Roulet Thomas, Alvarez R Michael
University of Cambridge, Cambridge, CB2 1TN UK.
California Institute of Technology, Pasadena, CA 91125 USA.
NPJ Clim Action. 2023;2(1):47. doi: 10.1038/s44168-023-00086-x. Epub 2023 Dec 18.
Identifying drivers of climate misinformation on social media is crucial to climate action. Misinformation comes in various forms; however, subtler strategies, such as emphasizing favorable interpretations of events or data or reframing conversations to fit preferred narratives, have received little attention. This data-driven paper examines online climate and sustainability communication behavior over 7 years (2014-2021) across three influential stakeholder groups consisting of eight fossil fuel firms (industry), 14 non-governmental organizations (NGOs), and eight inter-governmental organizations (IGOs). We examine historical Twitter interaction data ( = 668,826) using machine learning-driven joint-sentiment topic modeling and vector autoregression to measure online interactions and influences amongst these groups. We report three key findings. First, we find that the stakeholders in our sample are responsive to one another online, especially over topics in their respective areas of domain expertise. Second, the industry is more likely to respond to IGOs' and NGOs' online messaging changes, especially regarding environmental justice and climate action topics. The fossil fuel industry is more likely to discuss public relations, advertising, and corporate sustainability topics. Third, we find that climate change-driven extreme weather events and stock market performance do not significantly affect the patterns of communication among these firms and organizations. In conclusion, we provide a data-driven foundation for understanding the influence of powerful stakeholder groups on shaping the online climate and sustainability information ecosystem around climate change.
识别社交媒体上气候错误信息的驱动因素对气候行动至关重要。错误信息有多种形式;然而,一些较为微妙的策略,如强调对事件或数据的有利解读,或重新构建对话以符合偏好的叙述,却很少受到关注。这篇基于数据的论文研究了2014年至2021年这7年间,由八个化石燃料公司(行业)、14个非政府组织(NGO)和八个政府间组织(IGO)组成的三个有影响力的利益相关者群体的在线气候与可持续性传播行为。我们使用机器学习驱动的联合情感主题建模和向量自回归来研究历史推特互动数据(=668,826),以衡量这些群体之间的在线互动和影响。我们报告了三个关键发现。第一,我们发现样本中的利益相关者在网上彼此响应,尤其是在各自领域专业知识的主题上。第二,该行业更有可能对政府间组织和非政府组织的在线信息变化做出回应,特别是在环境正义和气候行动主题方面。化石燃料行业更有可能讨论公共关系、广告和企业可持续性主题。第三,我们发现气候变化驱动的极端天气事件和股票市场表现并未显著影响这些公司和组织之间的沟通模式。总之,我们为理解强大的利益相关者群体对塑造围绕气候变化的在线气候与可持续性信息生态系统的影响提供了一个基于数据的基础。