ANALYZING CORPORATE SUSTAINABILITY REPORTS WITH TEXT ANALYSIS METHOD: EVIDENCE FROM BIST SUSTAINABILITY 25 INDEX

G. Özer, Yavuz Selim Balcıoğlu, A. Merter, Sedat Çerez
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Abstract

Sustainability reports enable businesses to inform the public about their progress towards their goals, including environmental, social and management measures, and the risks they may face now or in the future. Because businesses play an active role in the sustainable development process, investors are more interested in the activities of businesses and the impact of these activities on the environment. In this study, the sustainability reports of the companies included in the Borsa Istanbul (BIST) sustainability 25 index were evaluated. Using a sample of 16 companies included in the Borsa Istanbul sustainability 25 index and publishing sustainability reports in 2021, text analysis was conducted to identify trends in sustainability reports. The analysis process was carried out using the Python programming language. According to the results of the analysis obtained, it was determined that 81% of the sustainability report statements showed positive sensitivity and 19% had negative sensitivity. In addition, in the study, LDA topic modeling and distance mapping were applied to 16 sustainability reports, and it was observed that reports 2, 15, 6, 13 and 8 overlapped with each other as a result of the application. It was assumed that there was no definitive word list for each report, as no heavy overlap was found between the other reports. Therefore, we can state that the PyLDAvis package included in the Python software is an effective tool for identifying overlaps and the most important themes among sustainability reports.
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用文本分析法分析企业可持续发展报告:来自bist可持续发展指数的证据
可持续发展报告使企业能够向公众通报其实现目标的进展情况,包括环境、社会和管理措施,以及他们现在或将来可能面临的风险。由于企业在可持续发展过程中发挥着积极的作用,投资者对企业的活动以及这些活动对环境的影响更感兴趣。本研究对Borsa Istanbul (BIST)可持续发展25指数中的公司的可持续发展报告进行了评价。以Borsa Istanbul可持续发展25指数中的16家公司为样本,并于2021年发布可持续发展报告,进行文本分析以确定可持续发展报告的趋势。分析过程使用Python编程语言进行。根据所获得的分析结果,确定81%的可持续发展报告报表具有正敏感性,19%具有负敏感性。此外,本研究对16份可持续发展报告应用了LDA主题建模和距离映射,发现报告2、15、6、13和8由于应用了LDA主题建模和距离映射,报告2、15、6、13和8相互重叠。假定每个报告没有确定的词表,因为在其他报告之间没有发现严重的重叠。因此,我们可以说Python软件中包含的PyLDAvis包是识别可持续发展报告中重叠和最重要主题的有效工具。
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