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Between left and right: A discourse network analysis of Universal Basic Income on Dutch Twitter

Published online by Cambridge University Press:  20 March 2023

Erwin Gielens*
Affiliation:
Department of Sociology, Tilburg University, the Netherlands
Femke Roosma
Affiliation:
Department of Sociology, Tilburg University, the Netherlands
Peter Achterberg
Affiliation:
Department of Sociology, Tilburg University, the Netherlands
*
*Corresponding author, email: erwin.gielens@gmail.com
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Abstract

Universal Basic Income (UBI) found its way back to media and policy agendas, presented as an alternative to the social investment policies omnipresent in Europe. In spite of the apparent appeal, however, UBI faces a discursive and political stalemate that seems hard to overcome. In an attempt to understand this tension, we explore the discursive coalitions surrounding UBI in a debate on Dutch Twitter. We use discourse network analysis to (a) cluster discussants endorsing similar positions and (b) see which political elites endorse these positions. We find that the known schism between the liberal and egalitarian interpretations of UBI is driven by ambivalence towards its redistributive implications. Moreover, we observe a turn towards social investment frames amongst UBI advocates, who centrally argue that UBI is activating and deregulating social security. This change in framing, however, seems to have little visible impact on elite coalition formation. Green-left elites remain overrepresented amongst proponents, while liberal and conservatives are opposed, and the socialist party remains divided on the issue. Thus, while the implementation of a ‘full’ UBI seems blocked by redistributive concerns, the social investment turn may be the political compromise that explains the popular appeal and political success of UBI inspired experiments.

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Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press
Figure 0

Figure 1. Number of tweets per day mentioning (or replying to tweets mentioning) basic income.

Figure 1

Figure 2. Occurrence frequency per concept.

Note: for interpretability we show only arguments with an adoption frequency of one percent.
Figure 2

Figure 3. Example connection in an actor network based on the underlying argument references.

Figure 3

Figure 4. The clustered actor network.

Note: For purposes of visualization the graph is based on agreement ties only. Node size is proportional to tie strength – larger nodes represent participants in stronger agreement with others. The graph layout is based on the Fruchterman-Reingold algorithm, where nodes in stronger agreement are placed closer together. Only ties with strength greater than the threshold .60 are plotted. Community detection partitioned the graph in 8 clusters (Q=.390), but 4 of these are very small. Since the four largest clusters contain 97.1% of all actors, we focus our interpretation on these four clusters.
Figure 4

Figure 5. Discursive positions of each cluster.

Note: for interpretability we show only arguments with at least one percent (k=45) of all concept references. A tweet example of each concept is available in Appendix A.Note: green cells indicate agreement with a concept, white cells indicate silence or ambivalence, and red cells indicate disagreement with a concept.
Figure 5

Figure 6. Concept network of the UBI debate on Dutch Twitter.

Note: Arguments are plotted using (absolute) radial centrality, meaning that more central arguments are closer to the center of the graph. Node size is proportional to degree centrality – larger squares represent concepts more frequenly used in conjunction with others. Tie width is proportional to strength of (dis)agreement. Tie colors represent connections made predominantly by the liberal-egalitarian cluster (green) or the opposition cluster (red) – deeper colors indicate stronger partisan connection. Only standardized ties stronger than the threshold .08 are plotted.
Figure 6

Table 1. Preliminary expectations

Figure 7

Table 2. Political elites endorsing each substantive position

Supplementary material: File

Gielens et al. supplementary material

Appendices A-E

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