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Corporate Social Responsibility Reports: Understanding Topics via Text Mining

机译:企业社会责任报告:通过文本挖掘了解主题

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This study utilizes Text Data Mining (TDM) to analyze the contents of Corporate Social Responsibility (CSR) Reports. The goal is to find evidence that environmental sustainability has become embedded in corporate policy and the core business discourse of seven organizations over 2004-2012. Results from supervised modeling techniques suggest embeddedness of environmental qualities in the business discourse. Unsupervised techniques provide additional support for embeddedness-as business topics tend to increasingly group with environmental ones. The process we outline should facilitate pattern discovery in documents, minimizing or eliminating the need for time-consuming content analysis that is frequently used in qualitative research. To our knowledge, this is one of the first attempts to apply TDM processing to analyze unstructured data from CSR reports.
机译:本研究利用文本数据挖掘(TDM)分析企业社会责任(CSR)报告的内容。目的是寻找证据,证明环境可持续性已在2004-2012年间嵌入到公司政策和七个组织的核心业务论述中。有监督的建模技术的结果表明,环境质量在商业话语中的嵌入性。无监督技术为嵌入性提供了额外的支持,因为业务主题趋向于与环境主题越来越紧密地结合在一起。我们概述的过程应有助于在文档中进行模式发现,从而最大程度地减少或消除对定性研究中经常使用的耗时的内容分析的需求。据我们所知,这是首次应用TDM处理来分析来自CSR报告的非结构化数据的尝试之一。

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