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What we tweet about when we tweet about taxes: a topic modelling approach
Puklavec, Žiga
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Kogler, Christoph
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Stavrova, Olga
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Zeelenberg, Marcel
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DOI:
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https://doi.org/10.1016/j.jebo.2023.07.005
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URL:
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https://www.sciencedirect.com/science/article/pii/...
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URN:
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urn:nbn:de:bsz:180-madoc-715049
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Document Type:
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Article
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Year of publication:
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2023
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The title of a journal, publication series:
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Journal of Economic Behavior & Organization : JEBO
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Volume:
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212
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Issue number:
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Special issue: The shadow economy, tax behaviour and institutions
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Page range:
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1242-1254
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Place of publication:
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Amsterdam [u.a.]
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Publishing house:
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Elsevier
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ISSN:
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0167-2681 , 1879-1751
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Publication language:
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English
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Institution:
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School of Social Sciences > Sozialpsychologie und Mikrosoziologie (Stavrova 2025-)
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Pre-existing license:
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 Creative Commons Attribution 4.0 International (CC BY 4.0)
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Subject:
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150 Psychology
300 Social sciences, sociology, anthropology
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Keywords (English):
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taxation , topic modeling , machine learning , social media , information diffusion , sentiment analysis
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Abstract:
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Recent literature on taxation suggests that a “service and client” approach by the authorities is required in order to establish a synergistic tax climate between taxpayers and tax offices and thus enhance voluntary tax compliance. The present study investigates whether lay people's conceptions about taxation reflect such a synergistic (vs. an antagonistic) climate. Applying an unsupervised machine learning approach (i.e., topic modeling) to over a million tax related tweets from 2010 to 2020, we identified 30 topics with different content. Using the theoretical framework differentiating between synergistic and antagonistic tax climate, we were able to further categorize these topics into four broader groups: 1. Opinions about Tax Politics, 2. Enforcement (antagonistic climate), 3. Information & Service (synergistic climate), and 4. Emotions. The most frequently observed group was Information & Service (synergistic climate), which also steadily gained prominence during the past decade. We proceeded by analyzing the information diffusion properties and sentiment of the tweets associated with the four groups. Information & Service tweets had the most positive sentiment but were shared the least, while tweets regarding Opinions about Tax Politics were shared most often. In sum, the results suggest that lay people's conceptions about taxation – as discerned from conversations on social media (Twitter) – largely reflect a synergistic (vs. an antagonistic) climate, and contribute to the literature on tax climate and social media.
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 | Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
 | Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation. |
 Search Authors in
BASE:
Puklavec, Žiga
;
Kogler, Christoph
;
Stavrova, Olga
;
Zeelenberg, Marcel
Google Scholar:
Puklavec, Žiga
;
Kogler, Christoph
;
Stavrova, Olga
;
Zeelenberg, Marcel
ORCID:
Puklavec, Žiga ; Kogler, Christoph ; Stavrova, Olga  ORCID: 0000-0002-6079-4151 ; Zeelenberg, Marcel
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