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Integrating XBRL data with textual information in Chinese: A semantic web approach

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  • Chou, Chi-Chun
  • Chang, C. Janie
  • Peng, Jacob

Abstract

Due to formatting differences, the difficulties of processing the textual disclosures and integrating them with quantitative financial data are well documented in the literature. Using a design science methodology, this paper describes a method that automatically extracts relevant textual data from annual reports published in Chinese. These extracted words are then mapped to a knowledge framework we proposed. This paper shows that it is technologically feasible to reorganize the MD&A contents into any given knowledge structure to improve the search capability, readability, and cohesiveness of the MD&A contents. Finally, we demonstrate a prototype system that uses semantic web technology to achieve information integration that presents XBRL formatted accounting data with relevant textual disclosures together to assist user decision making.

Suggested Citation

  • Chou, Chi-Chun & Chang, C. Janie & Peng, Jacob, 2016. "Integrating XBRL data with textual information in Chinese: A semantic web approach," International Journal of Accounting Information Systems, Elsevier, vol. 21(C), pages 32-46.
    • Handle: RePEc:eee:ijoais:v:21:y:2016:i:c:p:32-46
    DOI: 10.1016/j.accinf.2016.04.002
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    References listed on IDEAS

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    1. Christopher C. Yang & Johnny W.K. Luk & Stanley K. Yung & Jerome Yen, 2000. "Combination and boundary detection approaches on Chinese indexing," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(4), pages 340-351.
    2. Feng Li & Russell Lundholm & Michael Minnis, 2013. "A Measure of Competition Based on 10‐K Filings," Journal of Accounting Research, Wiley Blackwell, vol. 51(2), pages 399-436, May.
    3. O'Riain, Seán & Curry, Edward & Harth, Andreas, 2012. "XBRL and open data for global financial ecosystems: A linked data approach," International Journal of Accounting Information Systems, Elsevier, vol. 13(2), pages 141-162.
    4. Geerts, Guido L., 2011. "A design science research methodology and its application to accounting information systems research," International Journal of Accounting Information Systems, Elsevier, vol. 12(2), pages 142-151.
    5. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    6. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    7. Angela K. Davis & Isho Tama†Sweet, 2012. "Managers’ Use of Language Across Alternative Disclosure Outlets: Earnings Press Releases versus MD&A," Contemporary Accounting Research, John Wiley & Sons, vol. 29(3), pages 804-837, September.
    8. Boritz, J. Efrim & Hayes, Louise & Lim, Jee-Hae, 2013. "A content analysis of auditors' reports on IT internal control weaknesses: The comparative advantages of an automated approach to control weakness identification," International Journal of Accounting Information Systems, Elsevier, vol. 14(2), pages 138-163.
    9. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
    10. Stephen V. Brown & Jennifer Wu Tucker, 2011. "Large‐Sample Evidence on Firms’ Year‐over‐Year MD&A Modifications," Journal of Accounting Research, Wiley Blackwell, vol. 49(2), pages 309-346, May.
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    Cited by:

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    2. Eachempati, Prajwal & Srivastava, Praveen Ranjan & Kumar, Ajay & Tan, Kim Hua & Gupta, Shivam, 2021. "Validating the impact of accounting disclosures on stock market: A deep neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    3. Chou, Chi-Chun & Hwang, Nen-Chen Richard & Wang, Tawei & Debreceny, Roger, 2018. "The topical link model-integrating topic-centric information in XBRL-formatted reports," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 16-36.
    4. Sharifah Milda Amirul & Noor Ismawati Jaafar & Anna Azriati Che Azmi, 2022. "Two decades of XBRL: a science mapping of research trends and future research agenda," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2301-2324, August.
    5. Zhuoqian Liang & Ding Pan & Yuan Deng, 2020. "Research on the Knowledge Association Reasoning of Financial Reports Based on a Graph Network," Sustainability, MDPI, vol. 12(7), pages 1-14, April.
    6. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).

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