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 1965-2025, the
compound annual growth rate (CAGR) was +8.4%. The trend is
increasing (statistically significant; p < 0.05).
Mann
(1945);
Sen
(1968) The following years had unusually high publication activity:
2023, 2024, 2025.
Insights
The peer-reviewed share: 67.4 % recent
decade (2017–2026), up from 58.9 % previous decade (2007–2016).
Long-term trend (1965–2026): increasing. Note that 0% in the first year
of the period may reflect incomplete metadata rather than an actual
absence of peer review.
1867 publications (97%) scientific, 61 publications (3%) other.
Older years (1965–2018) aggregated for readability. Full timespan available in data export.
The Norwegian Publication Indicator (NPI), also known as the Norwegian list, classifies publication channels into two levels. Level 2 (top ~20% per field) is considered the most prestigious channels. Level 1 covers other approved channels.
A high proportion of publications (≥10%) lack NPI classification. Common causes: missing ISSN in source data, channels outside the register (~40,000 journals), conference series, or recently launched journals. See the journal table for unclassified channels.
DORA mode is enabled for this report. Bifrost evaluates the report against the principles of DORA (2012) and CoARA (2022).
The report contains elements that are not compatible with DORA principle 1: “Do not use journal-based metrics as a surrogate measure of the quality of individual research articles.”
NPI level classification (Level 1/2) is shown in the report. NPI is a Nordic classification system that ranks publication channels by academic standing, i.e. a channel-based ranking that DORA advises against using as a quality surrogate. The classification is presented here as descriptive information about publication patterns, not as a measure of individual article quality.
Researchers are listed below, sorted by scientific productivity.
Insights
The top 20% most productive researchers
account for 39% of publications (Gini 0.22, scale: 0 = even, 1 = fully
concentrated). Average number of co-authors: 2.4 recent decade
(2017–2026), up from 1.8 (2007–2016).
Insights
78 research groups of roughly equal
size; no single cluster dominates. Each researcher collaborates with an
average of 3.3 others (a moderately connected network). Clear cluster
structure (Modularity 0.98); researchers primarily work within their own
group. The network is sparse: only 1.0% of all researcher pairs have a
direct collaboration link.
Each node represents a researcher and each link a co-authorship. Colors indicate research groups (clusters) identified via modularity analysis. Node size reflects number of publications.
The co-authorship network is built from co-authored publications. Each node represents a researcher, and each edge is weighted by number of joint publications. Edge weights are normalized using association strength Van Eck et al. (2009) before clustering with the Louvain algorithm. Centrality measures: degree (number of collaborators), collaboration intensity (total co-authoring frequency), and bridge score (weighted betweenness using inverse weights) Newman (2004). Network density measures the proportion of realized vs. possible collaborations. Terminology: «Collaborators (avg)» = mean degree; «Clustering» = modularity Blondel et al. (2008).
Percentages are calculated on pairs where both authors have country data (2038 classified of 2040 total, coverage 100%). Of which 2 pairs where both authors lack institutional affiliation, 0 pairs where the institution could not be mapped to a country, and 0 pairs where one side lacks data.
‘Co-authored texts’ indicates the number of texts the author has written together with one or more co-authors.
Network statistics show central nodes in the collaboration network. Degree is the number of direct collaborations, while betweenness shows which authors act as bridges between different groups.
The first co-author listed is the one the author has written with the most times. ‘Number’ indicates the number of co-authored texts with the author. Up to four additional co-authors are listed, in descending order of co-authorship.
Below is a visualization of the 78 different groupings in the dataset. The colors indicate different groups.
Adaptive visualization (large): 335 nodes / 552 edges → 140 nodes / 232 edges after filtering.
The visualization was restored to the unfiltered source network: the adaptive filters would otherwise have reduced it below the threshold for a meaningful display.
Author names to the right; group ID to the left. You can see the size of the groups and the most common keywords of the groups in the tables that follow. A combination of search and sorting can be used to further explore group membership.
The table is limited to a) groups with more than 3 members; b) groups with at least one keyword in any publication; c) the ten most used keywords per group.
See also the supervisor and opponent network in the researcher section for an analysis of academic collaboration patterns beyond co-authorship.
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.
Insights
106 researchers have supervised or
opposed across institutional boundaries. Strongest connection: Dalarna
University – Karlstad University (Connection strength: 6). Based on
80.9% of dissertations with identifiable supervisors.
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
245 institutions contribute. Stockholms
universitet, Göteborgs universitet and Karlstads universitet account for
29 % — a broad distribution.
Overview of international collaboration based on co-authorship and affiliations in publications.
Insights
46 countries represented in
collaborations. United Kingdom, Finland and Norway are most common. 9.8
% of publications involve international co-authors — up from 7 %
(2007–2016) to 13 % (2017–2026).
Based on co-author affiliation country.
Insights:
The network comprises 98 institutions
with 272 collaboration relationships. The strongest collaboration is
between Stockholm University and Uppsala University (20
co-publications). Uppsala University has the most collaboration partners
(20).
The map primarily shows co-authorship between institutions. Supervisor/opponent links are shown as separate network relations and may be fewer, because only records with clear institutional affiliation can be included.
Insights
Social Sciences dominates (83 %).
Subject breadth has increased (1970–2026, H: 0.48 → 0.62). Moderate
interdisciplinarity — research combines related subject areas.
Rao-Stirling: 0.582 (where 0 = single discipline, 1 = maximum
diversity). Based on 5 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 1965–2026, 7.6% (146 of 1,928) publications lack subject classification at this level.
Proportion of total publications per year (%). Note that a publication may belong to multiple categories.
barn; socialvetenskap; learning; pedagogical work; historieämnen; lärande; språkvetenskap; etnicitet; nordiska språk; genus; history of ideas; övrig samhällsvetenskap; religious studies and theology; ekonomi; mathematics; teknikhistoria; social psychology; socialpsykologi; vårdvetenskap; idrottsvetenskap; biblioteks- och informationsvetenskap; elektronik; socialmedicin; artificial intelligence (ai); teknikvetenskap; idrott
Insights
Broad keyword profile — no single term
dominates (HHI: 0.0012 — Herfindahl-Hirschman Index, where 0 = perfectly
even distribution, 1 = one term dominates entirely). Most common is
“samhällskunskap” appearing in 12.4 % of publications, across a total of
4799.
education
Colors indicate frequency quantiles within this dataset.
Red: Highest frequency (12.4-9.94%); Blue: High frequency (9.94-7.48%); Green: Medium frequency (7.48-5.02%); Orange: Low frequency (5.02-2.56%); Gray: Lowest frequency (2.56-0.1%)
Rising keywords: samhällskunskap
Declining keywords: citizenship, citizenship education, civics, 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.
Below are deep-dive insights for rising keywords. Keywords marked with ↑ are statistically significant (p < 0.05), while those marked with ~ show strong correlations (|r| > 0.5) but lack statistical significance.
Burst periods:
Trend start: 2009 (6 pubs.)
The following keywords show a steady decline over the entire time period, without having had a distinct burst period previously:
A declining trend may reflect reduced research interest or a shift to newer terminology for the same research area.
Early publishers (1999–2006):
Researchers: Olson, Maria (2), Almgren, Nina (1), Bergström (fd Boman), Ylva (1)
Most active period (2014–2016, 41 publications):
Researchers: Olson, Maria (11), Dahlstedt, Magnus (9), Fejes, Andreas (9)
Institutions: Linköpings universitet (27), Stockholms universitet (11), Uppsala universitet (7)
Co-varying keywords: education, democracy, adult education
Last 3 years: 20 publications
Note: A declining trend may indicate terminological shift rather than decreased research interest.
Early publishers (2000–2007):
Researchers: Roth, Klas (2), Bergström (fd Boman), Ylva (1), Boman, Ylva (1)
Most active period (2014–2016, 29 publications):
Researchers: Fejes, Andreas (4), Olson, Maria (4), Sandahl, Johan (4)
Institutions: Linköpings universitet (13), Stockholms universitet (11), Karlstads universitet (5)
Co-varying keywords: education, democracy, social studies
Last 3 years: 12 publications
Note: A declining trend may indicate terminological shift rather than decreased research interest.
Early publishers (1985–1995):
Researchers: Bron Jr, Michal (6), Wojciechowska-Bron, Agnieszka (1)
Most active period (2009–2011, 18 publications):
Researchers: Eklund, Niklas (2), Larsson, Anna (2), Andersson, Ragnar (1)
Institutions: Karlstads universitet (8), Stockholms universitet (5), Umeå universitet (4)
Co-varying keywords: samhällskunskap, social studies, international education
Last 3 years: 15 publications
Note: A declining trend may indicate terminological shift rather than decreased research interest.
Early publishers (2000–2007):
Researchers: Olson, Maria (2), Boman, Ylva (1), Brock-Utne, Birgit (1)
Most active period (2013–2015, 14 publications):
Researchers: Olson, Maria (4), Dahlstedt, Magnus (3), Carpentier, Nico (2)
Institutions: Högskolan i Skövde (4), Linköpings universitet (4), Stockholms universitet (4)
Co-varying keywords: education, citizenship, citizenship education
Last 3 years: 9 publications
Note: A declining trend may indicate terminological shift rather than decreased 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: 2007–2020 (moderate burst)
Peak year: 2011 (10 pubs.)
Driving actors during period:
Co-varying keywords: samhällskunskap, social studies, ämnesdidaktik
Current status: Declining
Burst period: 2012–2019 (moderate burst)
Peak year: 2016 (17 pubs.)
Driving actors during period:
Co-varying keywords: education, utbildning och lärande, adult education
Current status: Declining
Burst period: 2013–2016 (moderate burst)
Peak year: 2015 (14 pubs.)
Driving actors during period:
Co-varying keywords: subject learning and teaching, ämnesdidaktik, citizenship
Current status: Declining
Burst period: 2013–2022 (moderate burst)
Peak year: 2015 (11 pubs.)
Driving actors during period:
Co-varying keywords: ämnesdidaktik, citizenship, samhällskunskap
Current status: Stable
Burst period: 2018–2021 (moderate burst)
Peak year: 2019 (17 pubs.)
Driving actors during period:
Co-varying keywords: samhällskunskap, civics, ämnesdidaktik med inriktning mot de samhällsvetenskapliga ämnenas didaktik
Current status: Rising
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: “education” (85%), “citizenship” (56%), “social”
(42%), “school” (32%), “swedish” (31%). These patterns reflect the
thematic core of the dataset. Note that geographic markers such as
“swedish” are common in academic metadata and reflect the national
affiliation of publications rather than the research topic.
Notice: The dataset contains 25931 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.
The first doctoral thesis in the dataset is from 1965, Samhällskunskap som skolämne: målsättningar, kursinnehåll och arbetssätt på den grundläggande skolans högstadium by Bromsjö, Birger. From then until 2026, a total of 178 theses have been registered. Of these, 148 are doctoral theses and 30 are licentiate theses.
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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