Voices from the far right: a text analysis of Swedish parliamentary debates

Abstract

In this paper we study the effects of a radical right party entering a national parliament, on the parliament discourse. We follow the classification developed by Meguid (2008) and use a probabilistic topic model approach to analyze the 300,000 speeches delivered in the Swedish parliament between 1994 and 2017. Our results indicate that immigration became a more prevalent topic in party leader debates when the Sweden Democrats entered the parliament in 2010. The other parties started to address immigration more, but still not to the extent that the Sweden Democrats did. In 2015, as Sweden faced a migration crisis, immigration became a more salient issue in the parliamentary debates. This could be seen as an external shock that forced the mainstream parties to put more emphasis on the topic of immigration. We conclude that the mainstream parties used a partly dismissive, partly adversarial strategy in their speeches when the SD entered the parliament. The migration crises in 2015 made them focus more on immigration and they thereby adopted a more adversarial strategy.

Seeded Topic Models in Digital Archives: Analyzing the Swedish Understanding of Immigration, 1945--2019

“…In the generative processes of the seeded topic model, we replace ϕ by the topic-word distribution φ, which is a K × V matrix with the informative prior placed on the seeded entries (Magnusson, Öhrvall, Barrling & Mimno 2018). In practice, informative priors are placed on the topic-word matrix such that a word used to guide the model has a zero probability of belonging to any other topic than the one for which it is a seed word.…”

“…We suggest an extension to the original topic model, the seeded topic model (Arora et al 2012, Jagarlamudi et al 2012, Magnusson, Öhrvall, Barrling & Mimno 2018, Watanabe & Zhou 2022 to act as a bridge between supervised and unsupervised approaches. The fully unsupervised nature of the original topic model does not guarantee finding a topic that meaningfully reflects a concept of interest.…”

Semantic tagging and the Nordic tradition of everyman’s rights

“…The method of seeded topic modelling would appear to us as a promising way to study specific themes in large textual corpora such as parliamentary debates (cf. Magnusson et al, 2018). 6 Cf.…”

Studying Ideational Change in Russian Politics with Topic Models and Word Embeddings

“…When other methods are used to reveal these perspectives, topic modeling can be used to offset the influence of thematic content of analyzed texts on the ideational perspective (Jelveh et al 2018;Lauderdale and Clark 2014). Other approaches suggest modification of the Topic Modeling algorithm in a way that assumes that word choice in texts is determined both by the ideological perspective and by the topic in the mainstream understanding of a term-the theme of a text (Magnusson et al 2018;Ahmed and Xing 2010).…”