文章基本信息

标题：About relationship between business text patterns and financial performance in corporate data
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作者：BangRae Lee ; BangRae Lee ; Jun-Hwan Park 等
期刊名称：Journal of Open Innovation: Technology, Market, and Complexity
电子版ISSN：2199-8531
出版年度：2018
卷号：4
期号：1
页码：1-18
DOI：10.1186/s40852-018-0080-9
语种：English
出版社：Springer
摘要：AbstractThis study uses text and data mining to investigate the relationship between the text patterns of annual reports published by US listed companies and sales performance. Taking previous research a step further, although annual reports show only past and present financial information, analyzing text content can identify sentences or patterns that indicate the future business performance of a company. First, we examine the relation pattern between business risk factors and current business performance. For this purpose, we select companies belonging to two categories of US SIC (Standard Industry Classification) in the IT sector, 7370 and 7373, which include Twitter, Facebook, Google, Yahoo, etc. We manually collect sales and business risk information for a total of 54 companies that submitted an annual report (Form 10-K) for the last three years in these two categories. To establish a correlation between patterns of text and sales performance, four hypotheses were set and tested. To verify the hypotheses, statistical analysis of sales, statistical analysis of text sentences, sentiment analysis of sentences, clustering, dendrogram visualization, keyword extraction, and word-cloud visualization techniques are used. The results show that text length has some correlation with sales performance, and that patterns of frequently appearing words are correlated with the sales performance. However, a sentiment analysis indicates that the positive or negative tone of a report is not related to sales performance.
关键词：Corporate annual report;10-k;Text mining;Business keyword;Financial performance;Keyword trends;Word cloud;Sentiment analysis;Correlation coefficient;Hierarchical clustering;Dendrogram