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題名 Opinion Mining for Relating Subjective Expressions and Annual Earnings in US Financial Statements
作者 張元晨
Chen,Chien-Liang ; Liu,Chao-Lin ; Chang,Yuan-Chen ; Tsai,Hsiang-Ping
貢獻者 財管系
關鍵詞 financial text mining ; opinion mining ; sentiment analysis ; financial multiword expressions ; natural language processing ; MPQA ; information extraction
日期 2013.07
上傳時間 19-Dec-2013 11:56:24 (UTC+8)
摘要 Financial statements contain quantitative information and manager’s subjective evaluation of firm’s financial status. Using information released in U.S. 10-K filings. Both qualitative and quantitative appraisals are crucial for quality financial decisions. To extract such opinioned statements from the reports, we built tagging models based on the conditional random field (CRF) techniques, considering a variety of combinations of linguistic factors including morphology, orthography, predicate-argument structure, syntax, and simple semantics. Our results show that the CRF models are reasonably effective to find opinion holders in experiments when we adopted the popular MPQA corpus for training and testing. The contribution of our paper is to identify opinion patterns in multiword expressions (MWEs) forms rather than in single word forms. We find that the managers of corporations attempt to use more optimistic words to obfuscate negative financial performance and to accentuate the positive financial performance. Our results also show that decreasing earnings were often accompanied by ambiguous and mild statements in the reporting year and that increasing earnings were stated in assertive and positive way.
關聯 Journal of Information Science and Engineering, 29(4), 743-764
資料類型 article
dc.contributor 財管系en_US
dc.creator (作者) 張元晨zh_TW
dc.creator (作者) Chen,Chien-Liang ; Liu,Chao-Lin ; Chang,Yuan-Chen ; Tsai,Hsiang-Pingen_US
dc.date (日期) 2013.07en_US
dc.date.accessioned 19-Dec-2013 11:56:24 (UTC+8)-
dc.date.available 19-Dec-2013 11:56:24 (UTC+8)-
dc.date.issued (上傳時間) 19-Dec-2013 11:56:24 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/62716-
dc.description.abstract (摘要) Financial statements contain quantitative information and manager’s subjective evaluation of firm’s financial status. Using information released in U.S. 10-K filings. Both qualitative and quantitative appraisals are crucial for quality financial decisions. To extract such opinioned statements from the reports, we built tagging models based on the conditional random field (CRF) techniques, considering a variety of combinations of linguistic factors including morphology, orthography, predicate-argument structure, syntax, and simple semantics. Our results show that the CRF models are reasonably effective to find opinion holders in experiments when we adopted the popular MPQA corpus for training and testing. The contribution of our paper is to identify opinion patterns in multiword expressions (MWEs) forms rather than in single word forms. We find that the managers of corporations attempt to use more optimistic words to obfuscate negative financial performance and to accentuate the positive financial performance. Our results also show that decreasing earnings were often accompanied by ambiguous and mild statements in the reporting year and that increasing earnings were stated in assertive and positive way.en_US
dc.format.extent 309851 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Journal of Information Science and Engineering, 29(4), 743-764en_US
dc.subject (關鍵詞) financial text mining ; opinion mining ; sentiment analysis ; financial multiword expressions ; natural language processing ; MPQA ; information extractionen_US
dc.title (題名) Opinion Mining for Relating Subjective Expressions and Annual Earnings in US Financial Statementsen_US
dc.type (資料類型) articleen