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政大機構典藏 > 商學院 > 財務管理學系 > 期刊論文 > Item 140.119/66213

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/66213

Title:	Opinion mining for relating multiword subjective expressions and annual earnings in US financial statements
Authors:	張元晨 Chen, Chien-Liang;Liu, Chao-Lin;Chang, Yuan-Chen;Tsai, Hsiangping
Contributors:	財管系
Keywords:	financial text mining, opinion mining, sentiment analysis, financial, multiword expressions, natural language processing, MPQA, information extraction
Date:	2013.03
Issue Date:	2014-05-26 10:28:08 (UTC+8)
Abstract:	Financial statements contain quantitative information and manager’s subjective evalua-tion of firm’s financial status. Using information released in U.S. 10-K filings. Both qualita-tive 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 ran-dom field (CRF) techniques, considering a variety of combinations of linguistic factors in-cluding morphology, orthography, predicate-argument structure, syntax, and simple seman-tics. 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 ob-fuscate 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.
Relation:	Journey of information Science and Engineering, Vol.29, No.3, pp.25-50
Data Type:	article
Appears in Collections:	[財務管理學系] 期刊論文

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