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- Fredén, Annika, et al.
(författare)
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Insurance Voting in the Centre: An Experimental Approach
- 2024
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Ingår i: International Journal of Public Opinion Research. - 1471-6909 .- 0954-2892. ; 36:3
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Tidskriftsartikel (refereegranskat)abstract
- Recent research suggests that to help their preferred coalition win an election, voters are willing to vote for a political party other than their preferred choice. In this field, voting for smaller parties under proportional representation is an under-studied feature. A crucial factor to estimate the chances for smaller parties is polls. In this study, we analyze the influence of opinion polls on switching vote choice to a smaller party when the party polls are at different levels. Building on an original survey experiment, we elaborate the potential differences in impact on insurance voting for a small party with looser or stronger association with a government alternative. The focus is the 2022 Swedish general election and the three smallest parties in parliament: the Green Party (center-left), the Christian Democrats (right), and the Liberals (center-right). The experiment had nine different conditions where each of these parties was placed at different levels of opinion: below, at, and above the parliamentary threshold, while holding all other factors constant. We find that poll-induced insurance voting is most prevalent for the party with the strongest preference for a government alternative (the Christian Democrats) and least prevalent for the party with a more issue-focused stance (the Greens).
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| 2. |
- Kokkinakis, Dimitrios, 1965, et al.
(författare)
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The Prevalence of mRNA Related Discussions during the Post-COVID-19 Era
- 2023
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Ingår i: Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. - : IOS Press. - 0926-9630 .- 1879-8365. - 9781643683881 ; 302, s. 798-802
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Konferensbidrag (refereegranskat)abstract
- Vaccinations are one of the most significant interventions to public health, but vaccine hesitancy and skepticism are raising serious concerns for a portion of the population in many countries, including Sweden. In this study, we use Swedish social media data and structural topic modeling to automatically identify mRNA-vaccine related discussion themes and gain deeper insights into how people's refusal or acceptance of the mRNA technology affects vaccine uptake. Our point of departure is a scientific study published in February 2022, which seems to once again sparked further suspicion and concern and highlight the necessity to focus on issues about the nature and trustworthiness in vaccine safety. Structural topic modelling is a statistical method that facilitates the study of topic prevalence, temporal topic evolution, and topic correlation automatically. Using such a method, our research goal is to identify the current understanding of the mechanisms on how the public perceives the mRNA vaccine in the light of new experimental findings.
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| 3. |
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| 4. |
- Saynova, Denitsa, et al.
(författare)
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Class Explanations: the Role of Domain-Specific Content and Stop Words
- 2023
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Ingår i: Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), pages 103–112, Tórshavn, Faroe Islands. - : University of Tartu Library.
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Konferensbidrag (refereegranskat)abstract
- We address two understudied areas related to explainability for neural text models. First, class explanations. What features are descriptive across a class, rather than explaining single input instances? Second, the type of features that are used for providing explanations. Does the explanation involve the statistical pattern of word usage or the presence of domain-specific content words? Here, we present a method to extract both class explanations and strategies to differentiate between two types of explanations – domain-specific signals or statistical variations in frequencies of common words. We demonstrate our method using a case study in which we analyse transcripts of political debates in the Swedish Riksdag.
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