Fredén Annika, Sikström Sverker
Department of Political, Historical, Religious and Cultural Studies Karlstad University Karlstad Sweden.
Department of Psychology Lund University Lund Sweden.
Soc Sci Q. 2021 Sep;102(5):2170-2183. doi: 10.1111/ssqu.13036. Epub 2021 Aug 6.
Previous research suggests that governments usually gain support during crises such as the Covid-19. However, these findings are based on rating scales that only allow us to measure the strength of this support. This article proposes a new measure of how voters evaluate Prime Ministers (PM) by asking for descriptive keywords that are analyzed by natural language processing.
By collecting a representative sample of citizens' own key words describing their PM in 15 countries in Europe during the outbreak of Covid-19, and analyzing these by latent semantic analysis and a multiple OLS regression, we could quantify the strength and direction of voters' view.
The strength analysis supported previous studies that describing the PM with positive words was strongly associated with vote intention. Furthermore, a change in the direction of the attitudes from "good" to "honest" was found. A new finding was that the pandemic was associated with an increase in polarization.
The keyword evaluation analysis provides opportunities of evaluating both strength and direction of voters' view of their PM, where we show new results related to increased polarization and shift in the direction of attitudes.
先前的研究表明，政府通常在诸如新冠疫情这样的危机期间获得支持。然而，这些发现基于评级量表，而这些量表仅能让我们衡量这种支持的强度。本文提出一种新的衡量方法，通过询问描述性关键词并利用自然语言处理进行分析，来了解选民如何评价总理。
通过收集在新冠疫情爆发期间欧洲15个国家公民描述其总理的代表性关键词样本，并通过潜在语义分析和多元OLS回归对这些关键词进行分析，我们能够量化选民观点的强度和方向。
强度分析支持了先前的研究，即用积极词汇描述总理与投票意向密切相关。此外，还发现了态度方向从“好”到“诚实”的转变。一个新发现是，疫情与两极分化加剧有关。
关键词评估分析为评估选民对其总理观点的强度和方向提供了机会，在此我们展示了与两极分化加剧和态度方向转变相关的新结果。
