IDEAS home Printed from https://ideas.repec.org/a/eee/ijoais/v38y2020ics1467089520300373.html
   My bibliography  Save this article

An ontological artifact for classifying social media: Text mining analysis for financial data

Author

Listed:
  • Alzamil, Zamil
  • Appelbaum, Deniz
  • Nehmer, Robert

Abstract

In this paper we utilize a structured natural language processing implementation of the Financial Industry Business Ontology (FIBO) to extract financial information from the unstructured textual data of the social media platform Twitter regarding financial and budget information in the public sector, namely the two public-private agencies of the Port Authority of NY and NJ (PANYNJ), and the NY Metropolitan Transportation Agency (MTA). This research initiative uses the Design Science Research (DSR) perspective to develop an artifact to classify tweets as being either relevant to financial bonds or not. We apply a frame and slot approach from the artificial intelligence and natural language processing literature to operationalize this artifact. FIBO provides standards for defining the facts, terms, and relationships associated with financial concepts. We show that FIBO grammar can be used to mine semantic meaning from unstructured textual data and that it provides a nuanced representation of structured financial data. With this artifact, social media such as Twitter may be accessed for the knowledge that its text contains about financial concepts using the FIBO ontology. This process is anticipated to be of interest to bond issuers, regulators, analysts, investors, and academics. It may also be extended towards other financial domains such as securities, derivatives, commodities, and banking that relate to FIBO ontologies, as well as more generally to develop a structured knowledge representation of unstructured data through the application of an ontology.

Suggested Citation

  • Alzamil, Zamil & Appelbaum, Deniz & Nehmer, Robert, 2020. "An ontological artifact for classifying social media: Text mining analysis for financial data," International Journal of Accounting Information Systems, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:ijoais:v:38:y:2020:i:c:s1467089520300373
    DOI: 10.1016/j.accinf.2020.100469
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1467089520300373
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.accinf.2020.100469?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Priyank Gandhi & Tim Loughran & Bill McDonald, 2019. "Using Annual Report Sentiment as a Proxy for Financial Distress in U.S. Banks," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(4), pages 424-436, October.
    2. Mattessich, Richard, 2003. "Accounting representation and the onion model of reality: a comparison with Baudrillard's orders of simulacra and his hyperreality," Accounting, Organizations and Society, Elsevier, vol. 28(5), pages 443-470, July.
    3. Adrian LUPASC & Ioana LUPASC & Gheorghe NEGOESCU, 2010. "The Role of Ontologies for Designing Accounting Information Systems," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 101-108.
    4. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nerantzidis, Michail & Tampakoudis, Ioannis & She, Chaoyuan, 2024. "Social media in accounting research: A review and future research agenda," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 54(C).
    2. Konstantinos Sikelis & George E. Tsekouras & Konstantinos Kotis, 2021. "Ontology-Based Feature Selection: A Survey," Future Internet, MDPI, vol. 13(6), pages 1-28, June.
    3. Fábio Albuquerque & Paula Gomes Dos Santos, 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools," FinTech, MDPI, vol. 2(2), pages 1-27, April.
    4. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
    2. Bilal Hafeez & M. Humayun Kabir & Udomsak Wongchoti, 2022. "Are retail investors really passive? Shareholder activism in the digital age," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(3-4), pages 423-460, March.
    3. Apostolos G. Katsafados & Dimitris Anastasiou, 2024. "Short-term prediction of bank deposit flows: do textual features matter?," Annals of Operations Research, Springer, vol. 338(2), pages 947-972, July.
    4. Tzomakas, Christos & Anastasiou, Dimitrios & Katsafados, Apostolos & Krokida, Styliani Iris, 2023. "Crisis sentiment and banks’ stock price crash risk: A missing piece of the puzzle?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 87(C).
    5. Dimitris Anastasiou & Apostolos Katsafados, 2023. "Bank deposits and textual sentiment: When an European Central Bank president's speech is not just a speech," Manchester School, University of Manchester, vol. 91(1), pages 55-87, January.
    6. Meng‐Feng Yen & Yu‐Pei Huang & Liang‐Chih Yu & Yueh‐Ling Chen, 2022. "A Two-Dimensional Sentiment Analysis of Online Public Opinion and Future Financial Performance of Publicly Listed Companies," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1677-1698, April.
    7. Jiao Ji & Oleksandr Talavera & Shuxing Yin, 2018. "The Hidden Information Content: Evidence from the Tone of Independent Director Reports," Working Papers 2018-28, Swansea University, School of Management.
    8. Umar, Tarik, 2022. "Complexity aversion when SeekingAlpha," Journal of Accounting and Economics, Elsevier, vol. 73(2).
    9. Drago, Carlo & Ginesti, Gianluca & Pongelli, Claudia & Sciascia, Salvatore, 2018. "Reporting strategies: What makes family firms beat around the bush? Family-related antecedents of annual report readability," Journal of Family Business Strategy, Elsevier, vol. 9(2), pages 142-150.
    10. Rybinski, Krzysztof, 2020. "The forecasting power of the multi-language narrative of sell-side research: A machine learning evaluation," Finance Research Letters, Elsevier, vol. 34(C).
    11. Rolf Uwe Fülbier & Thorsten Sellhorn, 2023. "Understanding and improving the language of business: How accounting and corporate reporting research can better serve business and society," Journal of Business Economics, Springer, vol. 93(6), pages 1089-1124, August.
    12. Chris Florakis & Christodoulos Louca & Roni Michaely & Michael Weber, 2020. "Cybersecurity Risk," Working Papers 2020-178, Becker Friedman Institute for Research In Economics.
    13. Liu, Pu & Nguyen, Hazel T., 2020. "CEO characteristics and tone at the top inconsistency," Journal of Economics and Business, Elsevier, vol. 108(C).
    14. Kladakis, George & Chen, Lei & Bellos, Sotirios K., 2023. "Ethical bank disclosures and liquidity creation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    15. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    16. Leilane de Freitas Rocha Cambara & Roberto Meurer, 2023. "News sentiment and foreign portfolio investment in Brazil," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3332-3348, July.
    17. Carlos Alberto Peláez & Andrés Solano, 2023. "A Practice for the Design of Interactive Multimedia Experiences Based on Gamification: A Case Study in Elementary Education," Sustainability, MDPI, vol. 15(3), pages 1-26, January.
    18. Tarek A Hassan & Stephan Hollander & Laurence van Lent & Ahmed Tahoun, 2019. "Firm-Level Political Risk: Measurement and Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 2135-2202.
    19. Eghbal Rahimikia & Stefan Zohren & Ser-Huang Poon, 2021. "Realised Volatility Forecasting: Machine Learning via Financial Word Embedding," Papers 2108.00480, arXiv.org, revised Mar 2023.
    20. Gao, Lei & Calderon, Thomas G. & Tang, Fengchun, 2020. "Public companies' cybersecurity risk disclosures," International Journal of Accounting Information Systems, Elsevier, vol. 38(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ijoais:v:38:y:2020:i:c:s1467089520300373. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-accounting-information-systems/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.