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Modelling taxpayers’ behaviour based on prediction of trust using sentiment analysis

Author

Listed:
  • Coita, Ioana-Florina
  • Belbe, Stefana (Ștefana)
  • Mare, Codruta (Codruța)
  • Osterrieder, Joerg
  • Hopp, Christian

Abstract

Fiscal systems depend on taxpayer's behaviour in terms of their willingness to comply or engage in fraud, deeply rooted in trustworthiness. To gain insights into taxpayers' perceptions and their influence on trust within taxation system, we use survey data to analyse word frequencies, sentiments, attitudes. Our approach utilizes natural language processing in conjunction with machine learning techniques. We highlight a notable correlation: taxpayers who lack trust in fiscal system tend to employ a higher frequency of negative words and exhibit limited word diversity in their expressions. The presence of negative sentiments may potentially foster fraudulent behaviours in the future.

Suggested Citation

  • Coita, Ioana-Florina & Belbe, Stefana (Ștefana) & Mare, Codruta (Codruța) & Osterrieder, Joerg & Hopp, Christian, 2023. "Modelling taxpayers’ behaviour based on prediction of trust using sentiment analysis," Finance Research Letters, Elsevier, vol. 58(PC).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323009212
    DOI: 10.1016/j.frl.2023.104549
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    More about this item

    Keywords

    Taxpayers’ behaviour; Theory of planned behaviour (TPB); Sentiment analysis; Behavioural modelling;
    All these keywords.

    JEL classification:

    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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