使用数据驱动的基于文档的方法自动化重要性评估

Matteo Francia, Enrico Gallinucci, Matteo Golfarelli
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引用次数: 0

摘要

重要性评估是公司了解其利益相关者对与环境、社会和治理问题相关的主题感兴趣的关键过程。重要性评估帮助企业确定其成长和沟通策略;最近,它在可持续发展报告中变得至关重要,即每年宣布以可持续的方式追求社会经济增长的活动的做法。在本文中,我们提出了一种数据驱动和自动化的方法来进行重要性评估。利益相关者对重要话题的看法是通过分析相关文本文件(例如,公司报告、新闻稿、社交媒体帖子),识别潜在有趣话题的提及,并将其转换为产生重要性排名或矩阵的分数来获得的。提出了一种迭代方法,通过逐步构建自动化过程所需的领域知识来增量地执行重要性评估。效率和有效性评估是在真实世界的场景中进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automating materiality assessment with a data-driven document-based approach
Materiality assessment is a critical process for companies to understand the interest perceived by its stakeholders towards topics related to environmental, social, and governance issues. Materiality assessment helps companies define their growth and communicative strategies; recently, it has become crucial within sustainability reporting, i.e., the practice of annually declaring the activities conducted to pursue economic growth in a sustainable way for society. In this paper, we propose a data-driven and automated approach to carry out materiality assessment. Stakeholders’ perception of important topics is obtained by analyzing relevant textual documents (e.g., company reports, press releases, social media posts), identifying mentions of potentially interesting topics, and converting them to scores that produce materiality rankings or matrices. An iterative methodology is proposed to incrementally carry out materiality assessment by progressively building the domain knowledge required to automate the process. Efficiency and effectiveness evaluations are carried out in a real-world scenario.
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CiteScore
19.20
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