{"title":"DisclosuR:通过创新的 R 软件包推进公司传播分析,增强文本洞察力","authors":"","doi":"10.1016/j.mex.2024.102909","DOIUrl":null,"url":null,"abstract":"<div><p>Firm and executive written communication allows researchers to explore firm strategy and executive personality. Two data sources have received increased interest in this matter: firm press releases and earnings call transcripts. However, while researchers can obtain these data sources through services like LexisNexis, they often come in unstructured formats that do not directly allow fine-grained quantitative analysis through statistical software. To address this challenge, we developed <em>disclosuR</em>, an innovative R package that transforms unstructured PDF press releases and earnings call transcripts into structured data frames, facilitating advanced text analysis. disclosuR stands out by providing unique features such as speaker-level language analysis and identifying temporal communication patterns within press releases. These functionalities empower researchers to conduct granular and reproducible quantitative analyses, significantly advancing the management literature. By enabling the seamless integration of text data into R, our package not only enhances the reproducibility of social science research but also opens new avenues for examining executive communication dynamics and strategic firm disclosures.</p><ul><li><span>•</span><span><p>Convert LexisNexis PDFs to structured R data frames</p></span></li><li><span>•</span><span><p>Standardize text analysis of firm communication</p></span></li></ul></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2215016124003613/pdfft?md5=db26612514181bbeab6a151542970365&pid=1-s2.0-S2215016124003613-main.pdf","citationCount":"0","resultStr":"{\"title\":\"DisclosuR: Advancing firm communication analysis through an innovative R package for enhanced textual insights\",\"authors\":\"\",\"doi\":\"10.1016/j.mex.2024.102909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Firm and executive written communication allows researchers to explore firm strategy and executive personality. Two data sources have received increased interest in this matter: firm press releases and earnings call transcripts. However, while researchers can obtain these data sources through services like LexisNexis, they often come in unstructured formats that do not directly allow fine-grained quantitative analysis through statistical software. To address this challenge, we developed <em>disclosuR</em>, an innovative R package that transforms unstructured PDF press releases and earnings call transcripts into structured data frames, facilitating advanced text analysis. disclosuR stands out by providing unique features such as speaker-level language analysis and identifying temporal communication patterns within press releases. These functionalities empower researchers to conduct granular and reproducible quantitative analyses, significantly advancing the management literature. By enabling the seamless integration of text data into R, our package not only enhances the reproducibility of social science research but also opens new avenues for examining executive communication dynamics and strategic firm disclosures.</p><ul><li><span>•</span><span><p>Convert LexisNexis PDFs to structured R data frames</p></span></li><li><span>•</span><span><p>Standardize text analysis of firm communication</p></span></li></ul></div>\",\"PeriodicalId\":18446,\"journal\":{\"name\":\"MethodsX\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2215016124003613/pdfft?md5=db26612514181bbeab6a151542970365&pid=1-s2.0-S2215016124003613-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MethodsX\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2215016124003613\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MethodsX","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2215016124003613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
公司和高管的书面交流使研究人员能够探索公司战略和高管个性。在这方面,有两个数据源受到越来越多的关注:公司新闻稿和收益电话记录。然而,虽然研究人员可以通过 LexisNexis 等服务获取这些数据源,但它们通常采用非结构化格式,无法直接通过统计软件进行精细的定量分析。为了应对这一挑战,我们开发了一个创新的 R 软件包 disclosuR,它能将非结构化的 PDF 新闻稿和盈利电话会议记录转化为结构化的数据框架,便于进行高级文本分析。这些功能使研究人员能够进行精细和可重复的定量分析,极大地推动了管理文献的发展。通过将文本数据无缝集成到 R 中,我们的软件包不仅提高了社会科学研究的可重复性,还为研究高管沟通动态和公司战略披露开辟了新途径。
DisclosuR: Advancing firm communication analysis through an innovative R package for enhanced textual insights
Firm and executive written communication allows researchers to explore firm strategy and executive personality. Two data sources have received increased interest in this matter: firm press releases and earnings call transcripts. However, while researchers can obtain these data sources through services like LexisNexis, they often come in unstructured formats that do not directly allow fine-grained quantitative analysis through statistical software. To address this challenge, we developed disclosuR, an innovative R package that transforms unstructured PDF press releases and earnings call transcripts into structured data frames, facilitating advanced text analysis. disclosuR stands out by providing unique features such as speaker-level language analysis and identifying temporal communication patterns within press releases. These functionalities empower researchers to conduct granular and reproducible quantitative analyses, significantly advancing the management literature. By enabling the seamless integration of text data into R, our package not only enhances the reproducibility of social science research but also opens new avenues for examining executive communication dynamics and strategic firm disclosures.
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Convert LexisNexis PDFs to structured R data frames