Retrieving, classifying and analysing narrative commentary in unstructured (glossy) annual reports published as PDF files

Retrieving, classifying and analysing narrative commentary in unstructured (glossy) annual reports published as PDF files
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检索、分类和分析以 PDF 文件形式发布的非结构化(光面)年度报告中的叙述性评论

DOI:
10.1080/00014788.2019.1609346
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发表时间:
2019
影响因子:
1.7
通讯作者:
El-Haj M
El-Haj M
中科院分区:
管理学4区
文献类型:
--
作者:
El-Haj M

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我们提供了一个方法论的贡献,开发,描述和评估的方法,自动检索和分析文本的数字PDF年度报告文件由上市公司在伦敦证券交易所(LSE)。检索方法保留了文件结构的信息,从而能够在报告的叙述部分和财务报表部分之间以及叙述部分内的各个章节之间进行明确划分。使用586份报告的随机样本进行手动验证,检索准确率超过95%。使用非金融伦敦证交所公司发布的报告的全面样本进行的大样本统计验证证实,报告的长度,叙述语气和(在较小程度上)可读性随经济和监管因素而变化。我们演示了如何适应非英语语言的文件和不同的监管制度,使用葡萄牙报告的案例研究的方法。我们使用该程序来构建新的研究资源,包括常见的年度报告部分的语料库和超过26,000个英国文本属性的数据集。年度报告。
We provide a methodological contribution by developing, describing and evaluating a method for automatically retrieving and analysing text from digital PDF annual report files published by firms listed on the London Stock Exchange (LSE). The retrieval method retains information on document structure, enabling clear delineation between narrative and financial statement components of reports, and between individual sections within the narratives component. Retrieval accuracy exceeds 95% for manual validations using a random sample of 586 reports. Large-sample statistical validations using a comprehensive sample of reports published by non-financial LSE firms confirm that report length, narrative tone and (to a lesser degree) readability vary predictably with economic and regulatory factors. We demonstrate how the method is adaptable to non-English language documents and different regulatory regimes using a case study of Portuguese reports. We use the procedure to construct new research resources including corpora for commonly occurring annual report sections and a dataset of text properties for over 26,000 U.K. annual reports.
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