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The Ties That Bind: Text Similarities and Conditional Diffusion among Parties

Published online by Cambridge University Press:  25 January 2021

Nils Düpont*
Affiliation:
Collaborative Research Center 1342, Global Dynamics of Social Policy, University of Bremen, Germany
Martin Rachuj
Affiliation:
Department of Political Science & Communication Studies, University of Greifswald, Germany
*
*Corresponding author. E-mail: duepont@uni-bremen.de
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Abstract

Comparative analyses of party policy diffusion are only just emerging. To better understand the conditions under which diffusion occurs, this article argues that three heuristics – availability, representativeness and anchoring – shape parties' efforts to gather information (from elsewhere), leading to differing diffusion effects. The study operationalizes the outcome as textual similarity of party manifestos in nineteen Western democracies from 1960 to 2016, applying a text-as-data approach and machine translation. Analyzing dyads, it assesses how commonalities and sender/receiver attributes impact diffusion. It finds that there is little room for cross-border diffusion as successful parties stick to their old program. Beyond the still-prevailing domestic context, ‘learning from cultural reference groups’ in a region is most important. In addition, diffusion appears within EP factions and transnational party organizations independently of the success/loss of the sender. The analysis thus sheds light on (un-)favorable conditions for party policy diffusion and paves the way for future studies applying machine translation and quantitative text analyses.

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Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Copyright
Copyright © The Author(s) 2021. Published by Cambridge University Press
Figure 0

Table 1. Operationalization of commonalities and attributes

Figure 1

Table 2. The impact of commonalities on text similarity

Figure 2

Figure 1. Conditional effect of sender and receiver attributes on text similarityNote: predictions with 90 per cent confidence intervals, adjusting for all other covariates and assuming RE = 0. The bottom graphs show the kernel density of observed data for Vote Gains/Losses.

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