Framing the Taxation-Democratization Link: An Automated Content Analysis of Cross-National Newspaper Data

Taxpaying constitutes a major opportunity for citizens to relate to their governments. Although it is true that paying taxes is a responsibility, it also entitles citizens to claim control over government spending, which may facilitate a greater democratization of a country’s political regime. Consistent with this reasoning, a growing body of scholarship has documented a positive relationship between the size of tax revenues extracted by the state and the adherence of the country’s regime to democratic values. What has been left underexplored is the role in this relationship of the media, a commonly available and relied-upon source of information about taxpaying for the public. This study offers a first contribution in this direction, by exploring the relationship between the nature of the political regime and the rhetorical construction of the concept of a taxpayer in the national press. Based on an automated content analysis of articles (N=24,969) published by ninety-two newspapers and news agencies in fifty-one countries using a set of pretrained and validated machine-learning algorithms, the study demonstrates that the less democratic a state is, the more likely it is for the national press to frame a taxpayer as a subordinate in a hierarchical relationship with the state, by discussing taxpaying in tax collection, rather than public spending, terms. The study furthers a more nuanced understanding of the place of the media in the taxation-democratization link and demonstrates the applicability of the supervised machine-learning approach to classifying frames in large cross-national samples of newspaper data.