Araştırma Makalesi
BibTex RIS Kaynak Göster

MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ

Yıl 2018, , 286 - 315, 22.06.2018
https://doi.org/10.31460/mbdd.349746

Öz

ÖZ

FİNANSAL RAPORLARIN ANALİZİNDE
METİN MADENCİLİĞİ KULLANIMI[1]

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 yönelmektedirler. 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
göstermek amaçlanmaktadır.

Anahtar Kelimeler:
Metin Madenciliği, Büyük Veri, Yapısal Olmayan Veri, Finansal Rapor, Faaliyet
Raporu, Finansal Olmayan Veri

Jel Kodları:M41,
C49















[1]
Bu çalışma “Finansal
Raporların Analizinde Metin Madenciliğinin Kullanımı:Borsa İstanbul Şirketlerinin
Kurumsal Yönetim Niteliklerinin Tahmini” adlı doktora tezinden türetilmiştir.





Kaynakça

  • Abrahamson, E. ve Park, C. 1994. “Concealment of Negative Organizational Outcomes:An Agency Theory Perspective”, Academy of Management Journal, 37 (5).
  • Abrahamson, E. ve Amir, E. 1996. “The Information Content of the President’s Letter to Shareholders”, Journal of Business Finance and Accounting, 23 (8).
  • Alwert, K., Bornemann, M. ve Will, Markus. 2009. “Does Intellectual Capital Reporting Matter to Financial Analysts?”, Journal of Intellecual 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 Frank, M.Z. 2004. “Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards”, The Journal of Finance, LIX (3).
  • Atan, S. “ Metin Madenciliği ile Sentiment Analizi ve Borsa İstanbul Uygulaması”, Ankara Üniversitesi Sosyal Bilimler Enstitüsü, Basılmamış Doktora Tezi, Ankara, 2016, s.248.
  • 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.,Hawley, J.P. ve Lee,Y.J. 2015. “Tracking “Real Time Corporate Sustainability Signals Using Cognitive Computing”, Journal of Applied Corporate Finance, 27 (2).
  • Balakrishnan, R. , Qiu, X.Y. ve Srinivasan, P. 2010. “On The Predictive Ability of Narrative Disclosures in Annual Reports”, European Journal of Operational Research, 202 (3).
  • Baginski, S.P. , Hassell, J.M. ve Kibrough, M.D. 2004. “Why Do Managemrs Explain Their Earnings Forecasts?”, Journal of Accounting Research, 42 (1).
  • Barkemeyer, R., Figge, F., Holt, D., Hahn, T. 2009. “What the Papers Say: Trends in Sustainability”, The Journal of Corporate Citizenship, 33.
  • Bogaerd, M.V.D. ve Aerts, W. 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., Aytuğ, H., Koehler, G., J. ve Pathak, P. 2010. “Making Words Work: Using Financial Text as a Predictor of Financial Events”, Decision Support Systems, 50 (2).
  • Chakraborty, V., Chiu, V. ve Vasarhelyi, M. 2014. “Automatic Classification of Accounting Literatüre”, International Journal of Accounting Information Systems, 15 (2).
  • Clatworthy, M.A. ve Jones,, M.J. 2003a. “Financial Reporting of Good News and Bad News: Evidence from Accounting Narratives”, Accounting, and Business Research, 33 (3).
  • Clatworthy, M.A. ve Jones,, M.J. 2006b. “Differential Patterns of Textual Characteristics and Company Performance in the Chairman’s Statement”, Accounting, Auditing and Accountability Journal, 19 (4).
  • Davis, A.K., Piger, J.M. ve Sedor, L.M. 2012. “Beyond the Numbers: Measuring the Information Content of Earnings Press Release Language”, Contemporary Accounting Resarch, 29 (3).
  • Demers, E. ve Vega, C. 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., Özdemir, T.G. ve Oğuz, D. 2009. Veri Madenciliğinde Yapısal Olmayan Verinin Analizi:Metin ve Web Madenciliği”, İstatistikçiler Dergisi, 2.
  • Eccles, R.G., Krzus, M., Tapscott, D. 2010. One Report, John Wiley&Sons Incorporated.
  • Fisher, I. E., Margaret R. G., Sunita, G., Kinsun T. 2010. “The Role of Text Analytics and Information Retrieval in the Accounting Domain”, Journal of Emerging Technologies in Accounting, 7.
  • Fisher, I.E., Garnsey, M.R. ve Hughes, M.E. 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, Ingram, R.W.ve Tennyson, B.M. 1984. “ A Methodology for the Analysis of Narrative Accounting Disclosures”, Journal of Accounting Research, 22 (1).
  • Francis, J. ve Schipper, K. 1999. “Have Financial Statements Lost Their Relevance?”, Journal of Accounting Research, 37 (2).
  • Gaikwad, S.V, Chaugule, A. ve Pramod P. 2014. “Text Mining Methods and Techniques”, International Journal of Computer Applications, 85 (17).
  • Gao, L., Chang, E. ve Han,S. 2007. “Powerful Tool to Expand Business Intelligence: Text Mining”, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 1 (8).
  • Gemar, G. ve Jimenez-Quintero, J.A. 2015. “Text Mining Social Media for Competitive Analysis”, Tourism ve Management Studies, 11 (1).
  • Glancy, F.H. ve Yadav, S.B. 2011. “A Computational Model for Financial Reporting Fraud Detection”, Decision Support Systems, 50 (3).
  • Goel, S., Gangolly, J., Faerman, S.R. ve Uzuner, O. 2010. “Can Linguistic Predictors Detect Fraudelent Financial Filings?”, Journal of Emerging Technologies in Accounting, 7.
  • Goel, S. ve Gangolly, J. 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 Gill, N.S. 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 Henriques, R. 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 Felden, C. 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., Moffitt, K.C., Burns, M.B., Burgoon, J.K. ve Felix, W.F.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:15.112016).
  • http://www.bb.itü.edu.tr (Erişim Tarihi:11.11.2016).
  • Jeong, H.,Ko, Y. ve Seo, J. 2016. “How to Improve Text Summarization and Classification by Mutual Cooperation on an Integrated Framework”, Expert Systems With Applications, 60.
  • Jusoh, S. ve Alfawareh, H. M. 2012. “Techniques, Applications and Challenging Issue in Text Mining”, International Journal of Computer Sciences Issues, 9 (6).
  • Kamaruddin, S.S., Bakar, A.A., Hamdan, A.R., Nor, F.M., Nazri, M.Z.A., Othman, Z.A. ve Hussein, G.S. 2015. “A Text Mining System for Deviation Detection in Financial Documents”, Intelligent Data Analysis, 19.
  • Kloptchenko, A.,Magnusson, C., Back, B., Visa, A. ve Vanharanta H. 2004a. “Mining Textual Contents of Financial Reports”, The International Journal of Digital Accounting Research, 4 (7).
  • Kloptchenko, A., Eklund, T., Karlsson, J., Back, B., Vanharanta, H. ve Visa, A. 2004b. “Combining Data and Text Mining Techniques for Analysing Financial Reports”, Intelligent Systems in Accounting, Finance and Management, 12.
  • Kothari, S.P., Li, X. Ve Short, J.E. 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 Ravi, V. 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 Zarowin, P. 1999. “The Boundaries of Financial Reporting and How to Extend Them”, Journal of Accounting Research, 37 (2).
  • Lev, B. ve Gu, F. 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., Adhitya, A. ve Srinivasan R. 2014. “Sustainability Trends in the Process Industries: A Text Mining-Based Analysis”, Computers in Industry, 65.
  • Liu, Y. ve Moffitt, K.C. 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 Mc Donald, B. 2011. “When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks”, The Journal of Finance, LXVI (1).
  • Matthies, B. ve Coners, A. 2015. “ Computer-Aided Text Analysis of Corporate Disclosures- Demonstration and Evaluation of Two Approaches”, The International Journal of Digital Accounting Research, 15.
  • Menon, R. ,Tong, L.H., Sathiyakeerthi, S., Brombacher, A. ve 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. Delen, D., Fast, A., Hill, T., Elder, J., ve Nisbet, B. 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 Mălăescu, I. 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 Skillicorn, D. 2014. “Accounting Variables, Deception, and A Bag of Words:Assesing the Tools of Fraud Detection”, Contemporary Accounting Research, 32 (3).
  • Rich, K.T., Roberts, B.L. ve Zhang, J.X. 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., Minsker, B.S., Work, Daniel B., Roth, D. 2014. “A Text Mining Framework for Advancing Sustainability Indicators”, Environmental Modelling&Software, 62.
  • Schumaker, R.P. ve Chen, H. 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., Issac, B. ve Modapothala, J.R. 2014. “Automatic Analysis of Corporate Sustainability Reports and Intelligent Scoring”, International Journal of Computational Intelligence and Applications, 13(1).
  • Shirata, C.Y. ve Sakagami, M. 2008. “An Analysis of the ‘‘Going Concern Assumption’’: Text Mining from Japanese Financial Reports”, Journal of Emerging Technologies in Accounting, 5.
  • Shirata, C.Y., Takeuchi, H., Ogino, S. ve Watanebe, H. 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 Smith, N.P. 1971. “Readability:A Measure of the Performance of the Communication Function of Financial Reporting”, The Accounting Review, 46 (3).
  • Soper, F.J. ve Dolphin, R. 1964. “Readability and Corporate Annual Reports”, The Accounting Review, 39 (2).
  • Şeker, Ş.E. 2015. “Metin Madenciliği (Text Mining)”, YBS Ansiklopedi, Cilt 2, Sayı 3, Eylül
  • 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., Saar-Tsechansky, M. ve Macskassy, S. 2008. “More Than Words:Quantifying Language to Measure Firms’ Fundamentals”, The Journal of Finance, LXIII (3).
  • Tsai, M.F., ve Wang, C.J. 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., Leung S., Permunetilleke D., Sankaran K., J. Zhang, Lam, W. 2008. “ Daily Stock Market Forecast from Textual Web Data”, Systems, Man, and Cybernetics,1998 IEEE International Conference.
  • Zaki, M. ve Theodoulidis, B. 2013 “Analyzing Financial Fraud Cases Using a Linguistics-Based Text Mining Approach”, Available at SSRN:
  • https://ssrn.com/abstract=2353834 or http://dx.doi.org/10.2139/ssrn.2353834
  • Zheng, Y. Ve Zhou, H. 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
Toplam 83 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İşletme
Bölüm ANABÖLÜM
Yazarlar

Şafak Ağdeniz

Birol Yıldız

Yayımlanma Tarihi 22 Haziran 2018
Gönderilme Tarihi 7 Kasım 2017
Yayımlandığı Sayı Yıl 2018

Kaynak Göster

APA Ağdeniz, Ş., & Yıldız, B. (2018). MUHASEBEDE ANALİZ YÖNTEMİ OLARAK METİN MADENCİLİĞİ. Muhasebe Bilim Dünyası Dergisi, 20(2), 286-315. https://doi.org/10.31460/mbdd.349746