Replication Data for: Greenwashing the Future? Computational Text Analysis of Environmental Reporting from the Fossil Fuel Industry

Achieving net zero greenhouse gas emissions by mid-century is central to climate policy agendas worldwide. As pressure mounts to show progress towards the energy transition, an increasing number of companies are committing to climate targets and risk engaging in “futurewashing”, a new form of misleading communication practice. Pairing the Net Zero Tracker dataset with a novel text corpus, this research uses computational methods to analyze forward-looking discourse in the sustainability reports of 97 fossil fuel companies on the Forbes Global 2000 list. After assessing climate target characteristics, a conventional keyword-based and more sophisticated large language model (LLM) approach are compared to capture future focus. This demonstrates that implementing a dynamic few-shot prompt with Meta’s Llama 3.1 405B model outperforms a custom-made dictionary classifier. Using the LLM, the prevalence of forward-looking statements is identified to measure future focus. This analysis finds that while future focus tends to be higher for companies with stronger climate targets, the prevalence of forward-looking statements varies greatly across the fossil fuel industry and suggests inconsistent messaging at the company level. Amid the proliferation of climate targets and the development of mandatory requirements for sustainability reporting, quantitative text analysis of corporate climate communication can contribute to an emerging understanding of “futurewashing” and provide empirical insights to inform policy practitioners.在本世纪中叶实现温室气体净零排放，是全球各国气候政策议程的核心目标。随着各界对能源转型进展的核查压力与日俱增，越来越多的企业纷纷承诺气候目标，同时也可能陷入"未来漂绿（futurewashing）"的风险——这是一种新型误导性传播行为。本研究将净零追踪器（Net Zero Tracker）数据集与全新文本语料库相结合，采用计算方法对《福布斯全球2000强》榜单中97家化石燃料企业的可持续发展报告中的前瞻性话语展开分析。在评估气候目标特征后，本研究对比了传统基于关键词的方法与更先进的大语言模型（Large Language Model，LLM）方法，以捕捉企业的未来关注焦点。研究结果表明，采用Meta公司Llama 3.1 405B模型搭配动态少样本（few-shot）提示词的方法，其表现优于定制化词典分类器。本研究借助大语言模型识别前瞻性陈述的占比，以此衡量企业的未来关注程度。分析结果显示，尽管气候目标更严苛的企业通常未来关注程度更高，但化石燃料行业内各企业的前瞻性陈述占比差异悬殊，这反映出不同企业在气候传播上存在表述不一致的问题。在气候目标层出不穷、可持续发展报告强制披露要求逐步完善的背景下，对企业气候传播开展量化文本分析，有助于深化学界对"未来漂绿"的认知，并为政策制定者提供实证参考依据。