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Enhancing the government accounting information systems using social media information: An application of text mining and machine learning

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  • Duan, Huijue Kelly
  • Vasarhelyi, Miklos A.
  • Codesso, Mauricio
  • Alzamil, Zamil

Abstract

This study demonstrates a way of bringing an innovative data source, social media information, to the government accounting information systems to support accountability to stakeholders and managerial decision-making. Future accounting and auditing processes will heavily rely on multiple forms of exogenous data. As an example of the techniques that could be used to generate this needed information, the study applies text mining techniques and machine learning algorithms to Twitter data. The information is developed as an alternative performance measure for NYC street cleanliness. It utilizes Naïve Bayes, Random Forest, and XGBoost to classify the tweets, illustrates how to use the sampling method to solve the imbalanced class distribution issue, and uses VADER sentiment to derive the public opinion about street cleanliness. This study also extends the research to another social media platform, Facebook, and finds that the incremental value is different between the two social media platforms. This data can then be linked to government accounting information systems to evaluate costs and provide a better understanding of the efficiency and effectiveness of operations.

Suggested Citation

  • Duan, Huijue Kelly & Vasarhelyi, Miklos A. & Codesso, Mauricio & Alzamil, Zamil, 2023. "Enhancing the government accounting information systems using social media information: An application of text mining and machine learning," International Journal of Accounting Information Systems, Elsevier, vol. 48(C).
    • Handle: RePEc:eee:ijoais:v:48:y:2023:i:c:s1467089522000525
    DOI: 10.1016/j.accinf.2022.100600
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    References listed on IDEAS

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    1. David F. Larcker & Anastasia A. Zakolyukina, 2012. "Detecting Deceptive Discussions in Conference Calls," Journal of Accounting Research, Wiley Blackwell, vol. 50(2), pages 495-540, May.
    2. Bernard J. Jansen & Mimi Zhang & Kate Sobel & Abdur Chowdury, 2009. "Twitter power: Tweets as electronic word of mouth," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(11), pages 2169-2188, November.
    3. Li, Feng, 2008. "Annual report readability, current earnings, and earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 45(2-3), pages 221-247, August.
    4. Jyoti Prakash Singh & Yogesh K. Dwivedi & Nripendra P. Rana & Abhinav Kumar & Kawaljeet Kaur Kapoor, 2019. "Event classification and location prediction from tweets during disasters," Annals of Operations Research, Springer, vol. 283(1), pages 737-757, December.
    5. Buchheit, Steve & Parsons, Linda M., 2006. "An experimental investigation of accounting information's influence on the individual giving process," Journal of Accounting and Public Policy, Elsevier, vol. 25(6), pages 666-686.
    6. Federica Farneti, 2009. "Balanced scorecard implementation in an Italian local government organization," Public Money & Management, Taylor & Francis Journals, vol. 29(5), pages 313-320, September.
    7. Reck, Jacqueline L., 2001. "The usefulness of financial and nonfinancial performance information in resource allocation decisions," Journal of Accounting and Public Policy, Elsevier, vol. 20(1), pages 45-71.
    8. Reed, Sarah A., 1986. "The impact of nonmonetary performance measures upon budgetary decision making in the public sector," Journal of Accounting and Public Policy, Elsevier, vol. 5(2), pages 111-140.
    9. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    10. 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.
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    1. Rajaa Ali Abed & Ahlam Hameed Kareem & Ali Khazaal Jabbar & Jasim Gshayyish zwaid & Hussein Falah Hasan, 2023. "The implementation of accounting information systems on the stock return and financial performance based on information technology (IT)," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 5(13 (125)), pages 57-64, October.

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