Context: Sustainable corporate behavior is increasingly valued by society and impacts corporate reputation and customer trust. Hence, companies regularly publish sustainability reports to shed light on their impact on environmental, social, and governance (ESG) factors. Problem: Sustainability reports are written by companies themselves and are therefore considered a company-controlled source. Contrary, studies reveal that non-corporate channels (e.g., media coverage) represent the main driver for ESG transparency. However, analysing media coverage regarding ESG factors is challenging since (1) the amount of published news articles grows daily, (2) media coverage data does not necessarily deal with an ESG-relevant topic, meaning that it must be carefully filtered, and (3) the majority of media coverage data is unstructured. Research Goal: We aim to extract ESG-relevant information from textual media reactions automatically to calculate an ESG score for a given company. Our goal is to reduce the cost of ESG data collection and make ESG information available to the general public. Contribution: Our contributions are three-fold: First, we publish a corpus of 432,411 news headlines annotated as being environmental-, governance-, social-related, or ESG-irrelevant. Second, we present our tool-supported approach called ESG-Miner capable of analyzing and evaluating headlines on corporate ESG-performance automatically. Third, we demonstrate the feasibility of our approach in an experiment and apply the ESG-Miner on 3000 manually labeled headlines. Our approach processes 96.7 % of the headlines correctly and shows a great performance in detecting environmental-related headlines along with their correct sentiment. We encourage fellow researchers and practitioners to use the ESG-Miner at https://www.esg-miner.com.

翻译：背景：社会日益重视企业的可持续行为，这直接影响企业声誉和客户信任。因此，企业定期发布可持续发展报告以阐明其对环境、社会和治理（ESG）因素的影响。问题：可持续发展报告由企业自行编制，属于企业可控的信息来源。然而，研究表明非企业渠道（如媒体报道）才是ESG透明度的主要驱动力。但分析媒体报道中的ESG因素存在三大挑战：（1）新闻文章数量持续增长；（2）媒体报道数据未必涉及ESG相关议题，需仔细筛选；（3）大部分媒体报道数据为非结构化数据。研究目标：我们旨在从文本形式的媒体反应中自动提取ESG相关信息，为指定企业计算ESG评分。目标降低ESG数据采集成本，使ESG信息惠及公众。贡献：本研究具有三重贡献：首先，我们发布了包含432,411条新闻标题的语料库，并对其标注为环境、治理、社会相关或非ESG类别。其次，我们提出了名为ESG-Miner的工具化方法，可自动分析评估企业ESG表现的新闻标题。最后，我们通过实验验证了方法的可行性，将ESG-Miner应用于3000条人工标注标题。该方法能正确处理96.7%的标题，在识别环境相关标题及其情感倾向方面表现优异。我们欢迎研究人员和从业者访问https://www.esg-miner.com使用ESG-Miner工具。