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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. Zhuk, Valerii & Pugachov, Mykola & Shpykuliak, Oleksandr & Bezdushna, Yuliya & Popko, Yevheniya, 2023. "Application of accounting for the assessment of war losses for agribusiness enterprises of Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(3), September.
    2. 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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