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

Coita, Ioana; Belbe, Stefana (Ștefana); Mare, Codruta (Codruța); Osterrieder, Jörg Robert; Hopp, Christian (2023). Modelling taxpayers’ behaviour based on prediction of trust using sentiment analysis Finance Research Letters, 58, p. 104549. Elsevier 10.1016/j.frl.2023.104549

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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.

Item Type:	Journal Article (Original Article)
Division/Institute:	Business School > Institute for Applied Data Science & Finance Business School > Institute for Applied Data Science & Finance > Finance, Accounting and Tax Business School
Name:	Coita, Ioana0000-0002-0782-2790; Belbe, Stefana (Ștefana); Mare, Codruta (Codruța); Osterrieder, Jörg Robert0000-0003-0189-8636 and Hopp, Christian0000-0002-4095-092X
Subjects:	H Social Sciences > HG Finance H Social Sciences > HJ Public Finance
ISSN:	15446123
Publisher:	Elsevier
Language:	English
Submitter:	Jörg Robert Osterrieder
Date Deposited:	03 May 2024 12:02
Last Modified:	03 May 2024 12:04
Publisher DOI:	10.1016/j.frl.2023.104549
Uncontrolled Keywords:	Taxpayers’ behaviour Theory of planned behaviour (TPB) Sentiment analysis Behavioural modelling
ARBOR DOI:	10.24451/arbor.21854
URI:	https://arbor.bfh.ch/id/eprint/21854