Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
How the coronavirus crisis affects citizen trust in institutions and in unknown others: Evidence from ‘the Swedish experiment’
2020195 citationsPeter Esaiasson et al.European Journal of Political Researchprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Peter Esaiasson
Since
Specialization
Citations
This map shows the geographic impact of Peter Esaiasson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peter Esaiasson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Esaiasson more than expected).
This network shows the impact of papers produced by Peter Esaiasson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peter Esaiasson. The network helps show where Peter Esaiasson may publish in the future.
Co-authorship network of co-authors of Peter Esaiasson
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Esaiasson.
A scholar is included among the top collaborators of Peter Esaiasson based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Peter Esaiasson. Peter Esaiasson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kölln, Ann‐Kristin, et al.. (2013). External efficacy and perceived responsiveness- same, same or different?. Data Archiving and Networked Services (DANS).6 indexed citations
Kokkonen, Andrej, Mikael Gilljam, & Peter Esaiasson. (2012). Migration Based Ethnic Diversity and Social Trust: A Multilevel Analysis of How Country, Neighborhood and Workplace Diversity Affects Social Trust in 22 Countries. SSRN Electronic Journal.1 indexed citations
9.
Esaiasson, Peter. (2011). Good Losers in Democracy. Statsvetenskaplig tidskrift. 113(1).1 indexed citations
10.
Kumlin, Staffan & Peter Esaiasson. (2011). Scandal Fatigue?: Scandal Elections and Satisfaction With Democracy in Europe 1977–2007. SSRN Electronic Journal.1 indexed citations
Esaiasson, Peter. (2010). Why Citizens (Sometimes) Dispute Public Facility Sitings in Their Neighborhood – An Experimental Account of the NIMBY-Syndrome. SSRN Electronic Journal.1 indexed citations
14.
Esaiasson, Peter, Mikael Gilljam, Henrik Oscarsson, & Lena Wängnerud. (2007). Metodpraktikan. Konsten att studera samhälle, individ och marknad.58 indexed citations
15.
Esaiasson, Peter, et al.. (1996). Svenska valfrågor. Partiernas valdebatt 1902-1994. Statsvetenskaplig tidskrift. 99(1).7 indexed citations
Holmberg, Sören & Peter Esaiasson. (1990). Makten i riksdagen. Statsvetenskaplig tidskrift. 93(2).
18.
Esaiasson, Peter. (1990). Svenska valkampanjer 1866-1988. Gothenburg University Publications Electronic Archive (Gothenburg University).21 indexed citations
19.
Esaiasson, Peter & Mikael Gilljam. (1985). Forskning kring parlament och parlamentariker. Statsvetenskaplig tidskrift. 88(4).1 indexed citations
20.
Esaiasson, Peter & Mikael Gilljam. (1983). Väljarna och de vilda strejkerna. Statsvetenskaplig tidskrift. 86(3).1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.