Key indicators summarise the report’s central metrics. All values are calculated from the underlying dataset and refer to the full period unless otherwise stated. Percentages (peer-reviewed, Open Access, international collaboration) are calculated as a share of total publications per year.
Percentage change is not shown when the base value is below 10 units, as small base values produce statistically unstable percentages (Hicks et al. (2015), principle 8; cf. CDC rule for n < 16). Absolute values are shown instead.
Insights
During the period 1992-2025, the
compound annual growth rate (CAGR) was +17.1%. The trend is
increasing (statistically significant; p < 0.05).
Mann
(1945);
Sen
(1968) The following years had unusually high publication activity:
2025.
Unlike the co-authorship analysis, which maps collaboration through joint publications, this section reveals the academic networks that emerge through dissertation supervision and opposition. Supervisors and opponents active at multiple institutions form informal knowledge bridges between organizations — relationships rarely captured by traditional bibliometric measures but which can reveal important patterns in academic knowledge transfer.
Warning: Affiliation data is missing for a large proportion of supervisors/opponents. Results should be interpreted with caution.
Insights
1 researchers have supervised or
opposed across institutional boundaries. Strongest connection:
Hälsohögskolan – Jönköping University (Connection strength: 2). Based on
0.1% of dissertations with identifiable supervisors.
Rankings are not reliable due to incomplete data. The list is shown in alphabetical order.
The supervisor/opponent network is separate from the international collaboration map. The map is based on co-authorship between author affiliations, while supervisor/opponent relations are shown in the network below.
The network is based on supervisor and opponent relationships extracted from SwePub records. Connection strength is calculated as (number of supervisions × 2) + (number of oppositions × 1). The weighting (2:1) is a Bifrost convention reflecting that supervision is a longer and deeper collaborative relationship than opposition. The method lacks established bibliometric practice; it was developed specifically for Bifrost.
The supervisor:opponent weighting (2:1) is a Bifrost convention to reflect the supervisor’s greater role in the dissertation process. This is not established bibliometric practice.
Insights
9 institutions contribute. Örebro
universitet, Högskolan i Jönköping and Karlstads universitet account for
60 % — a moderately concentrated distribution.
Insights
Social Sciences dominates (97 %).
Subject breadth is stable (1992–2025, H: 0.20 → 0.15). Moderate
interdisciplinarity — research combines related subject areas.
Rao-Stirling: 0.509 (where 0 = single discipline, 1 = maximum
diversity). Based on 6 HSV main areas (Swedish classification).
Rao-Stirling
(Stirling, 2007)
Shannon H (evenness index) measures how evenly publications are distributed across subject areas. A value of 1.00 means perfect evenness; lower values indicate dominance by individual areas. Rao-Stirling measures interdisciplinarity by weighing both the distribution and the taxonomic distance between subject areas according to the Swedish classification system. The scale ranges from 0 (all publications in one subject) to 1 (maximum spread across distant subject areas).
Proportion of total publications per year (%). Note that a publication may belong to multiple categories.
During 1992–2025, 6.1% (104 of 1,718) publications lack subject classification at this level.
Proportion of total publications per year (%). Note that a publication may belong to multiple categories.
genus; lärande; learning; etnicitet; barn; ekonomi; artificiell intelligens (ai); artificial intelligence (ai); fysiologi; teckenspråk; livsmedelshygien; näringslära; bildanalys; socialpsykologi
Insights
Broad keyword profile — no single term
dominates (HHI: 5e-04 — Herfindahl-Hirschman Index, where 0 = perfectly
even distribution, 1 = one term dominates entirely). Most common is
“demokrati” appearing in 4.2 % of publications, across a total of
4732.
education; samhällskunskap; social studies
Colors indicate frequency quantiles within this dataset.
Red: Highest frequency (4.2-3.38%); Blue: High frequency (3.38-2.56%); Green: Medium frequency (2.56-1.74%); Orange: Low frequency (1.74-0.92%); Gray: Lowest frequency (0.92-0.1%)
Declining keywords: democracy
The time series shows keywords that occur in at least 50 publications across the period. Values are shares of yearly publications to enable comparison between years of different total volume.
No rising trends were identified. Below are deep-dive insights for declining keywords instead. These may indicate subject areas decreasing in relevance or research interest.
The following keywords had periods of high activity in the past but have since declined. The analysis shows when they peaked, what drove the interest, and how activity has evolved since.
Burst period: 2017–2023 (moderate burst)
Peak year: 2019 (6 pubs.)
Driving actors during period:
Co-varying keywords: samhällskunskap, elever, teachers
Current status: Potentially rising
Burst period: 2018–2023 (moderate burst)
Peak year: 2022 (5 pubs.)
Driving actors during period:
Co-varying keywords: samhällskunskap, demokrati, upper secondary school
Current status: Rising
Burst period: 2017–2019 (moderate burst)
Peak year: 2018 (10 pubs.)
Driving actors during period:
Co-varying keywords: sverige, gender roles, hållbar utveckling
Current status: Potentially rising
Burst period: 2017–2019 (moderate burst)
Peak year: 2018 (9 pubs.)
Driving actors during period:
Co-varying keywords: sweden, eu, hållbar utveckling
Current status: Potentially declining
The heatmap shows how often keywords co-occur in the same publications. Association strength Van Eck et al. (2009) normalizes co-occurrence by the product of the individual keyword frequencies. Red asterisks (✱) in the upper-right corner of cells mark statistically significant co-occurrences (p < 0.05).
Keywords that frequently co-occur in the same publications form thematic clusters. The table below summarizes the clusters; the interactive graph shows the relationships visually.
The network diagram shows how keywords relate to each other based on co-occurrence in publications. Larger nodes mean more frequent keywords. Lines show co-occurrence. Colors indicate thematic clusters identified using the Leiden algorithm (Traag et al., 2019).
The frequency of individual words in the dataset as a whole. Words have been taken from title, abstract, and keywords. “Frequency” is total uses, including the number of mentions in the same text, while “publications” is the number of unique texts where the word appears.
Insights
The 5 most common words (by share of
publications) are: “social” (29%), “samhällskunskap” (28%), “kvalitativ”
(26%), “school” (26%), “studien” (25%). These patterns reflect the
thematic core of the dataset.
Notice: The dataset contains 27249 rows. For best performance, only the 8000 with the highest frequency are displayed in the table.
Here is a summary of word stems, i.e. parts of words, in the dataset as a whole. Words have been taken from title, abstract, and keywords. “Frequency” is total uses, including the number of mentions in the same text, while “publications” is the number of unique texts where the word appears.
These trends are indicative and complement the keyword analysis above.
Methodological note: Word frequency analysis is based on individual words extracted from title, abstract, and keywords. Unlike author-selected keywords, individual words can be noisier and more ambiguous — for example, the word ‘system’ may appear in both technical and social science contexts, while the keyword ‘adaptive systems’ is more precise. Stricter thresholds are used (minimum 10 occurrences, correlation > 0.5) and academic stopwords are excluded.
Rising/declining shows trends over time (Spearman correlation). New/disappearing shows lifecycle — when words started or stopped being used.
No statistically significant trends were identified among the most common words.
A complete list of the search results. Initially sorted by year (descending) and author (ascending). Change the order at the column header. Search can be done over all displayed fields.
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