Automatic Assessment of Information Disclosure Quality in Chinese Annual Reports

摘要：

　　Information disclosure in annual reports is a mandatory re quirement for publicly traded companies in China.The quality of in formation disclosure will reduce information asymmetry and therefore support market efficiency.Currently, the evaluation of the information disclosure quality in Chinese reports is conducted manually.It remains an untapped field for NLP and text mining community.The goal of this paper is to develop automatic assessment system for information disclo sure quality in Chinese annual reports.Our assessment system framework incorporates different technologies including Chinese document model ing, Chinese readability index construction, and multi-class classifica tion.Our explorative and systematic experiment results show that: 1) our automatic assessment system can produce solid predictive accuracy for disclosure quality, especially in excellent and fall categories; 2) our system for Chinese annual reports assessment achieves better predic tive accuracy in certain perspective than the counterparts of the English annual reports prediction; 3) our readability index for Chinese docu ments, as well as other findings from system performance, may provide enlightenment for a better understanding about the quality features of Chinese company annual reports.

关键词： Text classification Natural language processing Information disclosure quality Application

作者: Xin Ying Qiu Shengyi Jiang Kebin Deng

作者单位: CISCO School of Informatics Guangdong University of Foreign Studies, Guangzhou, China School of Finance Guangdong University of Foreign Studies, Guangzhou, China

会议类型: 国际会议

会议名称: Second CCF Conference,NLPCC2013(第二届自然语言处理与中文计算会议)

会议地点: 重庆

会议语种:英文

页码: 288-298

在线出版日期: 2013-11-15（万方平台首次上网日期，不代表论文的发表时间）