MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ

Birol YILDIZ, (Eskişehir Osmangazi Üniversitesi, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümü, Muhasebe ve Finansman Ana Bilim Dalı)
Şafak AĞDENİZ (Eskişehir Osmangazi Üniversitesi, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümü, Muhasebe ve Finansman Ana Bilim Dalı)
Muhasebe Bilim Dünyası Dergisi
19 0
Yıl: 2018 Cilt: 20 Sayı: 2 Sayfa Aralığı: 286 - 315 Metin Dili: Türkçe DOI: 10.31460/mbdd.349746 İndeks Tarihi: 25-03-2021

MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ

Öz:
İşletme ile ilgili alınacak kararlarda menfaat sahiplerinin ilk başvurduğu kaynak genel amaçlı finansal tablolardır. Genel amaçlı finansal tablolardan işletme ile ilgili tüm bilgilerin elde edilmesi mümkün değildir. Bu nedenle menfaat sahipleri başka kaynaklara yönelmektedir. Faaliyet raporları, sürdürülebilirlik raporları, entegre raporlar bu kaynaklara örnek olarak verilebilir. Ancak burada bu raporlarda yer alan verilerin analizi menfaat sahipleri için bir sorun olmaktadır. Çünkü büyük oranda yapısal olmayan veri içeren bu raporların analizinde mevcut istatistiksel yöntemler yetersiz kalmaktadır. Metin madenciliği bu soruna çözüm getiren ve muhasebe alanında da son yıllarda sıklıkla kullanılan bir büyük veri analiz yöntemidir. Bu çalışmada muhasebe alanında metin madenciliği çalışmaları incelenerek, metin madenciliğinin muhasebe alanında uygulama alanları hakkında araştırmacılara yol gösterilmesi amaçlanmaktadır.
Anahtar Kelime:

TEXT MINING AS AN ANALYZING METHOD IN ACCOUNTING

Öz:
General purpose financial statements are the first reference guide of the stakeholders. All of the information about the company can not be attained from general purpose financial statements. So, stakeholders turn to other sources. Annual reports, sustainability reports, integrated reporting can be given as an example for these sources. But, analyzing the data that included in these reports has been a problem for the stakeholders. Because, available statistical techniques are insufficient in analyzing these reports that contain too much unstructered data. Text mining is a big data analyzing method that used to solve this problem. Also, it has been using in accounting frequently in recent years. The aim of this study is to guide researchers about text mining application fields in accounting by searching the studies.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • Abrahamson, E. ve C. Park. 1994. “Concealment of Negative Organizational Outcomes:An Agency Theory Perspective”, Academy of Management Journal, 37(5).
  • Abrahamson, E. ve E. Amir. 1996. “The Information Content of the President’s Letter to Shareholders”, Journal of Business Finance and Accounting, 23(8).
  • Alwert, K., M. Bornemann ve M. Will. 2009. “Does Intellectual Capital Reporting Matter to Financial Analysts?”, Journal of Intellectual Capital, 10(3).
  • Amir, E., ve B. Lev. 1996. “Value-Relevance of Nonfinancial Information: The Wireless Communications Industry”, Journal of Accounting and Economics, 22.
  • Antweiler, W. ve M.Z. Frank. 2004. “Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards”, The Journal of Finance, LIX(3).
  • Atan, S. 1996. “Metin Madenciliği ile Sentiment Analizi ve Borsa İstanbul Uygulaması”, Ankara Üniversitesi Sosyal Bilimler Enstitüsü, Basılmamış Doktora Tezi, Ankara.
  • Atan, S. 2016. “Veri, Büyük Veri ve İşletmecilik”, Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 19(35).
  • Aureli, S. 2017. “ A Comparison of Content Analysis Usage and Text Mining in CSR Corporate Disclosure”, The International Journal of Digital Accounting Research, 17.
  • Bala, G., B., H.,J.P. Hawley ve Y.J. Lee. 2015. “Tracking “Real Time Corporate Sustainability Signals Using Cognitive Computing”, Journal of Applied Corporate Finance, 27(2).
  • Balakrishnan, R., X.Y. Qiu ve P. Srinivasan. 2010. “On The Predictive Ability of Narrative Disclosures in Annual Reports”, European Journal of Operational Research, 202(3).
  • Baginski, S.P., J.M. Hassell ve M.D. Kibrough. 2004. “Why Do Managemrs Explain Their Earnings Forecasts?”, Journal of Accounting Research, 42(1).
  • Barkemeyer, R., F. Figge, D. Holt ve T. Hahn. 2009. “What the Papers Say: Trends in Sustainability”, The Journal of Corporate Citizenship, 33.
  • Bogaerd, M.V.D. ve W. Aerts. 2011. “Applying Machine Learning in Accounting Research”, Expert Systemes with Applications, 38.
  • Cecchini, M. 2005. “Quantifying the Risk of Financial Events Using Kernel Methods and Information Retrieval”, University of Florida, Doctorate Dissertation.
  • Cecchini, M., H. Aytuğ, G. Koehler ve P. Pathak. 2010. “Making Words Work: Using Financial Text as a Predictor of Financial Events”, Decision Support Systems, 50(2).
  • Chakraborty, V., V. Chiu ve M. Vasarhelyi. 2014. “Automatic Classification of Accounting Literatüre”, International Journal of Accounting Information Systems, 15(2).
  • Clatworthy, M.A. ve M.J. Jones. 2003a. “Financial Reporting of Good News and Bad News: Evidence from Accounting Narratives”, Accounting, and Business Research, 33(3).
  • Clatworthy, M.A. ve M.J. Jones. 2006b. “Differential Patterns of Textual Characteristics and Company Performance in the Chairman’s Statement”, Accounting, Auditing and Accountability Journal, 19(4).
  • Davis, A.K., J.M. Piger ve L.M. Sedor. 2012. “Beyond the Numbers: Measuring the Information Content of Earnings Press Release Language”, Contemporary Accounting Resarch, 29(3).
  • Demers, E. ve C. Vega. 2008. “Soft Information in Earnings Announcements:News or Noise?”, Board of Governors of the Federal Reserve System International Finance Discussion Papers, No:951.
  • Dolgun, M.Ö., T.G. Özdemir ve D. Oğuz. 2009. Veri Madenciliğinde Yapısal Olmayan Verinin Analizi:Metin ve Web Madenciliği”, İstatistikçiler Dergisi, 2.
  • Eccles, R.G., M. Krzus ve D. Tapscott. 2010. One Report, John Wiley&Sons Incorporated.
  • Fisher, I.E., R.G. Margaret, G. Sunita ve T. Kinsun. 2010. “The Role of Text Analytics and Information Retrieval in the Accounting Domain”, Journal of Emerging Technologies in Accounting, 7.
  • Fisher, I.E., M.R. Garnsey ve M.E. Hughes. 2016. “Natural Language Processing in Accounting, Auditing and Finance:A Synthesis of the Literature with a Roadmap for Future Research”, Intelligent Systems in Accounting, Finance and Management, 23.
  • Fraizer, K.B, R.W. Ingram ve B.M. Tennyson. 1984. “A Methodology for the Analysis of Narrative Accounting Disclosures”, Journal of Accounting Research, 22(1).
  • Francis, J. ve K. Schipper. 1999. “Have Financial Statements Lost Their Relevance?”, Journal of Accounting Research, 37(2).
  • Gaikwad, S.V, A. Chaugule ve P. Pramod. 2014. “Text Mining Methods and Techniques”, International Journal of Computer Applications, 85(17).
  • Gao, L., E. Chang ve S. Han. 2007. “Powerful Tool to Expand Business Intelligence: Text Mining”, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 1(8).
  • Gemar, G. ve J.A. Jimenez-Quintero. 2015. “Text Mining Social Media for Competitive Analysis”, Tourism ve Management Studies, 11(1).
  • Glancy, F.H. ve S.B. Yadav. 2011. “A Computational Model for Financial Reporting Fraud Detection”, Decision Support Systems, 50(3).
  • Goel, S., J. Gangolly, S.R. Faerman ve O. Uzuner. 2010. “Can Linguistic Predictors Detect Fraudelent Financial Filings?”, Journal of Emerging Technologies in Accounting, 7.
  • Goel, S. ve J. Gangolly. 2012. “Beyond the Numbers:Mining the Annual Reports for Hidden Cues Indicative of Financial Statement Fraud”, Intelligent Systems in Accounting, Finance and Management, 19.
  • Gupta, R. ve N.S. Gill. 2012. “Financial Statement Fraud Detection Using Text Mining”, International Journal of Advanced Computer Science and Applications, 3(12).
  • Gürsakal, N. 2014. Büyük Veri, Dora Yayınları, Bursa.
  • Hajek, P. ve R. Henriques. 2017. “Mining Corporate Annual Reports for Intelligent Detection of Financial Statement Fraud – A Comparative Study of Machine Learning Methods”, Knowledge- Based Systems, 128.
  • Heidari,M. ve C. Felden. 2015. “Financial Footnote Analysis:Developing a Text Mining Approach”, Proceedings of the International Conference on Data Mining (DMIN); Athens: 10-16. Athens: The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing.
  • Holton,C. 2009. “Identifying Disgruntled Employee Systems Fraud Risk Through Text Mining: A Simple Solution for a Multi-Billion Dollar Problem”, Decision Support Systems, 46(4).
  • Humpherys, S.L., K.C. Moffitt, M.B. Burns, J.K. Burgoon ve W.F. Felix. 2011. “Identification of Fraudulent Financial Statements Using Linguistic Credibility Analysis”, Decision Support Systems, 50(3).
  • https://tr.wikipedia.org/wiki/Do%C4%9Fal_dil_i%C5%9Fleme, (Erişim Tarihi:15.11.2016).
  • http://www.bb.itü.edu.tr (Erişim Tarihi:11.11.2016).
  • Jeong, H., Y. Ko ve J. Seo. 2016. “How to Improve Text Summarization and Classification by Mutual Cooperation on an Integrated Framework”, Expert Systems With Applications, 60.
  • Jusoh, S. ve H.M. Alfawareh. 2012. “Techniques, Applications and Challenging Issue in Text Mining”, International Journal of Computer Sciences Issues, 9(6).
  • Kamaruddin, S.S., A.A. Bakar, A.R. Hamdan, F.M. Nor, M.Z.A. Nazri, Z.A. Othman ve Hussein, G.S. 2015. “A Text Mining System for Deviation Detection in Financial Documents”, Intelligent Data Analysis, 19.
  • Kloptchenko, A., C. Magnusson, B. Back, A. Visa ve H. Vanharanta. 2004a. “Mining Textual Contents of Financial Reports”, The International Journal of Digital Accounting Research, 4(7).
  • Kloptchenko, A., T. Eklund, J. Karlsson, B. Back, H. Vanharanta ve A. Visa. 2004b. “Combining Data and Text Mining Techniques for Analysing Financial Reports”, Intelligent Systems in Accounting, Finance and Management, 12.
  • Kothari, S.P., X. Li ve J.E. Short. 2009. “The Effect of Disclosures by Management, Analysts, and Business Press on Cost of Capital, Return Volatility, and Analyst Forecasts: A Case Study Using Content Analysis”, The Accounting Review, 84(5).
  • Kumar, B.S. ve V. Ravi. 2016. “A Survey of the Applications of Text Mining in Financial Domain”, Knowledge Based Systems, 114.
  • Lev, B. 1989. “On the Uselfulness of Earnings and Earnings Research: Lessons and Directions from Two Decades of Empirical Research”, Journal of Accounting Research, 27 (Supplement).
  • Lev, B. 2003. “Remarks on the Measurement, Valuation, and Reporting of Intangible Assets”, Economy policy Review, 9(3).
  • Lev, B. ve P. Zarowin. 1999. “The Boundaries of Financial Reporting and How to Extend Them”, Journal of Accounting Research, 37(2).
  • Lev, B. ve F. Gu. 2016. The End of Accounting and the Path Forward for Investors and Managers, John Wiley and Sons Inc.
  • Li, F. 2006. “Do Stock Market Investors Understand the Risk Sentiment of Corporate Annual Reports?”, Unpublished Working Paper, University of Michigan, Available at SSRN: https://ssrn.com/abstract=898181 or http://dx.doi.org/10.2139/ssrn.898181
  • Li, F. 2008a. “Annual Report Readability, Current Earnings and Earnings Persistance”, Journal of Accounting and Economics, 45(2-3).
  • Li, F. 2008b. “The Determinants and Information Content of the Forward-Looking Statements in Corporate Filings- A Naive Bayesian Machine Learning Approach”, Journal of Accounting Research, 48(5).
  • Li, F. 2010. “Textual analysis of Corporate Disclosures: A Survey of the Literature”, Journal of Accounting Literature”, 29.
  • Liew, W.T., A. Adhitya ve R. Srinivasan. 2014. “Sustainability Trends in the Process Industries: A Text Mining-Based Analysis”, Computers in Industry, 65.
  • Liu, Y. ve K.C. Moffitt. 2016. “Text Mining to Uncover the Intensity of SEC Comment Letters and Its Association with the Probability of 10-K Restatement”, Journal of Emerging Technolohies in Accounting, 13(1).
  • Loughran, T. ve B. Mc Donald. 2011. “When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks”, The Journal of Finance, LXVI(1).
  • Matthies, B. ve A. Coners. 2015. “Computer-Aided Text Analysis of Corporate Disclosures- Demonstration and Evaluation of Two Approaches”, The International Journal of Digital Accounting Research, 15.
  • Menon, R., L.H. Tong, S. Sathiyakeerthi, A. Brombacher ve C. Leong, C. 2004. “The Needs and Benefits of Appliying Textual Data Mining Within the Product Development Process”, Quality and Reliability Engineering International, 20.
  • Miner, G., D. Delen, A. Fast, T. Hill, J. Elder ve B. Nisbet. 2012. Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications, Elsevier, USA
  • Oğuzlar, A. 2011. Temel Metin Madenciliği, Dora Yayınları, Bursa
  • Pencle, N. ve I. Mălăescu. 2016. “What’s in the Words? Development and Validation of a Multidimensional Dictionary for CSR and Application Using Prospectuses”, Journal Emerging Technologies in Accounting, 13(2).
  • Purda, L. ve D. Skillicorn. 2014. “Accounting Variables, Deception, and A Bag of Words:Assesing the Tools of Fraud Detection”, Contemporary Accounting Research, 32(3).
  • Rich, K.T., B.L. Roberts, ve J.X. Zhang. 2016. “Linguistic Tone of Municipal Management Discussion and Analysis Disclosures and Future Financial Reporting Delays”, Journal of Emerging Technologies in Accounting, 13(2).
  • Rimerman, T.W. 1990. “The Changing Significance of Financial Statements”, Journal of Accountancy, 169(4).
  • Rivera, S.J., B.S. Minsker, D.B. Work ve D. Roth. 2014. “A Text Mining Framework for Advancing Sustainability Indicators”, Environmental Modelling&Software, 62.
  • Schumaker, R.P. ve H. Chen. 2006. “Textual Analysis of Stock Market Prediction Using Financial News Articles”, Proceedings of the Twelfth Americas Conference on Information Systems, Acapulcı, Mexico.
  • Shahi, A.M., B. Issac ve J.R. Modapothala. 2014. “Automatic Analysis of Corporate Sustainability Reports and Intelligent Scoring”, International Journal of Computational Intelligence and Applications, 13(1).
  • Shirata, C.Y. ve M. Sakagami. 2008. “An Analysis of the ‘‘Going Concern Assumption’’: Text Mining from Japanese Financial Reports”, Journal of Emerging Technologies in Accounting, 5.
  • Shirata, C.Y., H. Takeuchi, S. Ogino ve H. Watanebe. 2011. “Extracting Key Phrases as Predictors od Corporate Bankruptcy:Empirical Analysis of Annual Reports by Text Mining”, Journal of Emerging Technologies in Accounting, 8.
  • Smith, J.E. ve N.P. Smith. 1971. “Readability:A Measure of the Performance of the Communication Function of Financial Reporting”, The Accounting Review, 46(3).
  • Soper, F.J. ve R. Dolphin. 1964. “Readability and Corporate Annual Reports”, The Accounting Review, 39(2).
  • Şeker, Ş.E. 2015. “Metin Madenciliği (Text Mining)”, YBS Ansiklopedi, 2(3).
  • Tettlock, P.C. 2007. “Giving Content to Investor Sentiment: The Role of Media in the Stock Market”, The Journal of Finance, LXII(3).
  • Tettlock, P.C., M. Saar-Tsechansky ve S. Macskassy. 2008. “More Than Words:Quantifying Language to Measure Firms’ Fundamentals”, The Journal of Finance, LXIII(3).
  • Tsai, M.F., ve C.J. Wang. 2017. “On the Risk Prediction and Analysis of Soft Information in Finance Reports”, European Journal of Operational Research, 217.
  • Tunalı, V. 2011. “Metin Madenciliği İçin İyileştirilmiş Bir Kümeleme Yapısının Tasarımı ve Uygulaması”, Marmara Üniversitesi, Fen bilimleri Enstitüsü, Doktora Tezi.
  • Wuthrich B., V Cho., S. Leung, D. Permunetilleke, K. Sankaran, J. Zhang ve W. Lam. 2008. “Daily Stock Market Forecast from Textual Web Data”, Systems, Man, and Cybernetics,1998 IEEE International Conference.
  • Zaki, M. ve B. Theodoulidis. 2013. “Analyzing Financial Fraud Cases Using a Linguistics- Based Text Mining Approach”, Available at SSRN: https://ssrn. com/abstract =2353 83 4 or http://dx.doi.org/10.2139/ssrn.2353834
  • Zheng, Y. ve H. Zhou. 2012. “An Intelligent Text Mining System Applied to SEC Documents”, IEEE/ACIS 11th International Conference on Computer and Information Science.
  • TMS 1 Finansal Tabloların Sunuluşu Standardı Türkiye Muhasebe ve Finansal Raporlama Standartları Kavramsal Çerçeve 1 Seri Nolu Muhasebe Sistemi Uygulama Genel Tebliği
APA Yıldız B, AGDENIZ S (2018). MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. , 286 - 315. 10.31460/mbdd.349746
Chicago Yıldız Birol,AGDENIZ SAFAK MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. (2018): 286 - 315. 10.31460/mbdd.349746
MLA Yıldız Birol,AGDENIZ SAFAK MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. , 2018, ss.286 - 315. 10.31460/mbdd.349746
AMA Yıldız B,AGDENIZ S MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. . 2018; 286 - 315. 10.31460/mbdd.349746
Vancouver Yıldız B,AGDENIZ S MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. . 2018; 286 - 315. 10.31460/mbdd.349746
IEEE Yıldız B,AGDENIZ S "MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ." , ss.286 - 315, 2018. 10.31460/mbdd.349746
ISNAD Yıldız, Birol - AGDENIZ, SAFAK. "MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ". (2018), 286-315. https://doi.org/10.31460/mbdd.349746
APA Yıldız B, AGDENIZ S (2018). MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. Muhasebe Bilim Dünyası Dergisi, 20(2), 286 - 315. 10.31460/mbdd.349746
Chicago Yıldız Birol,AGDENIZ SAFAK MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. Muhasebe Bilim Dünyası Dergisi 20, no.2 (2018): 286 - 315. 10.31460/mbdd.349746
MLA Yıldız Birol,AGDENIZ SAFAK MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. Muhasebe Bilim Dünyası Dergisi, vol.20, no.2, 2018, ss.286 - 315. 10.31460/mbdd.349746
AMA Yıldız B,AGDENIZ S MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. Muhasebe Bilim Dünyası Dergisi. 2018; 20(2): 286 - 315. 10.31460/mbdd.349746
Vancouver Yıldız B,AGDENIZ S MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. Muhasebe Bilim Dünyası Dergisi. 2018; 20(2): 286 - 315. 10.31460/mbdd.349746
IEEE Yıldız B,AGDENIZ S "MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ." Muhasebe Bilim Dünyası Dergisi, 20, ss.286 - 315, 2018. 10.31460/mbdd.349746
ISNAD Yıldız, Birol - AGDENIZ, SAFAK. "MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ". Muhasebe Bilim Dünyası Dergisi 20/2 (2018), 286-315. https://doi.org/10.31460/mbdd.349746
Sayfa Oluşturulma Tarihi
26-04-2024 5:11

İLETİŞİM

TÜBİTAK ULAKBİM TR Dizin

Yüzüncüyıl, İşçi Blokları Mahallesi

Muhsin Yazıcıoğlu Caddesi No:51/C

06530 Çankaya / ANKARA +90 (312) 298 92 00

trdizin@tubitak.gov.tr

TÜBİTAK ULAKBİM Ulusal Akademik Ağ ve Bilgi Merkezi Cahit Arf Bilgi Merkezi © Tüm Hakları Saklıdır. Gizlilik Politikası Kullanım Şartları