Dimension Reduction
2026-02-05
LU BOWEN 488222
Loading the data
ess<-read.csv("C:/Users/13640/Desktop/ESS11e04_1.csv", header=TRUE)
set.seed(123)
ess <- do.call(
rbind,
lapply(
split(ess, ess$cntry),
function(x) x[sample(nrow(x), min(5, nrow(x))), ]
)
)Inspect the variables
Based on the variable inspection, the trust indicators can be clearly grouped into two broad categories. The first group concerns trust in political and public institutions, including trust in politicians, the police, parliament, political parties, the legal system, the European Parliament, and the United Nations. The second group reflects more general views of other people, covering whether others are seen as trustworthy, helpful, and fair. While the former captures attitudes toward institutions and authority, the latter reflects everyday, interpersonal forms of social trust.
From a data perspective, all variables are measured on the same scale, which makes them directly comparable. After removing non-substantive codes, the variables show no systematic missing patterns or abnormal distributions. This suggests that both institutional and social trust can be treated as different facets within a common trust framework, making the data suitable for further dimensionality reduction.
The descriptive statistics show that institutional and social trust variables follow broadly similar but clearly distinguishable distributional patterns. Within institutional trust, trust levels vary noticeably across different institutions. Trust in the police and the legal system is relatively high, with median values generally around 6 to 7, while trust in politicians and political parties is substantially lower, with medians leaning toward the lower half of the scale. This indicates that, in the European sample, public confidence in concrete political actors is weaker than trust in executive and judicial institutions.
Attitudes toward supranational institutions fall somewhere in between. Trust in the European Parliament and the United Nations tends to cluster around moderate values, suggesting a certain degree of acceptance, though not reaching the levels observed for domestic legal or law-enforcement institutions.
Social trust shows a more stable and moderate pattern. Evaluations of whether other people can be trusted, are helpful, or behave fairly are mostly concentrated around the middle of the scale, with relatively few extreme responses. This suggests that social trust is expressed more as an everyday, cautious attitude rather than a strong or polarized judgment.
It should also be noted that some variables include observations coded as 88, which in the ESS dataset indicate non-substantive responses rather than genuine trust scores. These values were treated appropriately in the subsequent analysis to prevent them from distorting the statistical results and the dimensionality reduction.
Overall, the distributions of these variables capture both internal differences within institutional trust and a clear distinction between institutional and social trust, providing a solid basis for extracting underlying trust dimensions in the following analysis.
trust_vars <- c(
"trstplt", "trstplc", "trstprl", "trstprt", "trstlgl",
"trstep", "trstun",
"ppltrst", "pplhlp", "pplfair"
)
trust_data <- ess[, trust_vars]
str(trust_data)## 'data.frame': 150 obs. of 10 variables:
## $ trstplt: int 9 2 2 8 2 6 3 5 3 4 ...
## $ trstplc: int 10 9 8 8 8 8 10 7 7 6 ...
## $ trstprl: int 9 2 4 8 5 5 5 5 6 5 ...
## $ trstprt: int 8 2 2 9 2 5 3 5 6 4 ...
## $ trstlgl: int 9 9 7 9 6 8 5 6 7 4 ...
## $ trstep : int 9 2 4 8 2 5 3 5 6 4 ...
## $ trstun : int 10 1 5 8 2 5 5 6 6 5 ...
## $ ppltrst: int 9 3 8 7 6 7 5 7 7 6 ...
## $ pplhlp : int 8 6 8 8 6 8 5 5 8 5 ...
## $ pplfair: int 7 8 7 8 7 8 7 7 8 7 ...colSums(is.na(trust_data))## trstplt trstplc trstprl trstprt trstlgl trstep trstun ppltrst pplhlp pplfair
## 0 0 0 0 0 0 0 0 0 0summary(trust_data)## trstplt trstplc trstprl trstprt
## Min. : 0.00 Min. : 0.000 Min. : 0.0 Min. : 0.000
## 1st Qu.: 2.00 1st Qu.: 5.000 1st Qu.: 3.0 1st Qu.: 2.000
## Median : 3.00 Median : 7.000 Median : 5.0 Median : 4.000
## Mean : 6.02 Mean : 7.353 Mean : 6.9 Mean : 6.447
## 3rd Qu.: 6.00 3rd Qu.: 8.000 3rd Qu.: 7.0 3rd Qu.: 6.000
## Max. :88.00 Max. :88.000 Max. :88.0 Max. :88.000
## trstlgl trstep trstun ppltrst
## Min. : 0.000 Min. : 0.00 Min. : 0.0 Min. : 0.00
## 1st Qu.: 4.000 1st Qu.: 3.00 1st Qu.: 3.0 1st Qu.: 3.25
## Median : 6.000 Median : 5.00 Median : 5.0 Median : 5.00
## Mean : 8.193 Mean : 7.04 Mean : 9.1 Mean : 4.86
## 3rd Qu.: 8.000 3rd Qu.: 6.00 3rd Qu.: 7.0 3rd Qu.: 7.00
## Max. :88.000 Max. :88.00 Max. :88.0 Max. :10.00
## pplhlp pplfair
## Min. : 0.000 Min. : 0.000
## 1st Qu.: 3.250 1st Qu.: 4.250
## Median : 5.000 Median : 6.000
## Mean : 5.513 Mean : 6.253
## 3rd Qu.: 7.000 3rd Qu.: 8.000
## Max. :88.000 Max. :88.000trust_data[trust_data > 10] <- NA
trust_data <- na.omit(trust_data)PCA
Before the analysis, all trust variables were standardized to have the same mean and variance. This step ensures that no single item dominates the results simply because it shows larger variation. Based on the standardized data, principal component analysis (PCA) was applied to reduce dimensionality and to examine whether the different trust indicators share a simpler underlying structure.
The PCA results show that the trust variables are not scattered across many unrelated dimensions, but instead cluster strongly around a small number of components. The first principal component alone explains about 56.6% of the total variance, indicating that most trust-related questions reflect a common overall trust tendency. The second principal component explains a further 14.6% of the variance, bringing the cumulative explained variance of the first two components to over 70%. In contrast, the remaining components contribute relatively little additional information.
Overall, these results suggest that trust attitudes in the European context can be summarized by a small number of core dimensions. Retaining the first two principal components is sufficient to capture the main structure of trust in the data, while additional components offer limited interpretive value.
trust_data <- scale(trust_data)
pca_trust <- prcomp(trust_data, center = FALSE, scale. = FALSE)
summary(pca_trust)## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 2.3795 1.2076 0.83867 0.76766 0.69119 0.56586 0.51429
## Proportion of Variance 0.5662 0.1458 0.07034 0.05893 0.04777 0.03202 0.02645
## Cumulative Proportion 0.5662 0.7120 0.78239 0.84132 0.88909 0.92111 0.94756
## PC8 PC9 PC10
## Standard deviation 0.48014 0.43978 0.31697
## Proportion of Variance 0.02305 0.01934 0.01005
## Cumulative Proportion 0.97061 0.98995 1.00000eigenvalues & Percentage of explained variances
Scree Plot：eigenvalues
This figure is used to determine how many principal components should be retained. The eigenvalue of the first component is clearly much larger than those of the remaining components, and there is a steep drop from PC1 to PC2. After the second component, the curve becomes noticeably flatter. This “elbow” pattern indicates that most of the information is concentrated in the first one or two components, while additional components contribute very little new information.
Based on this pattern, retaining two principal components appears to be the most reasonable choice, as it captures the main structure of the data without introducing dimensions with limited explanatory value. #### Plot 2：Percentage of explained variances This figure shows the proportion of total variance explained by each principal component. The results indicate that the first component alone accounts for about 56.6% of the variance and therefore plays a dominant role. The second component explains a further 14.6%, bringing the cumulative explained variance of the first two components to over 70%.
This pattern suggests that the trust variables are not randomly distributed, but can be effectively summarized by a small number of dimensions. From the third component onward, the explained variance drops substantially, and the additional components contribute little to the overall structure.
eigenvalues <- pca_trust$sdev^2
round(eigenvalues, 3)## [1] 5.662 1.458 0.703 0.589 0.478 0.320 0.264 0.231 0.193 0.100fviz_eig(pca_trust, choice='eigenvalue') ## Warning in geom_bar(stat = "identity", fill = barfill, color = barcolor, :
## Ignoring empty aesthetic: `width`.
fviz_eig(pca_trust) ## Warning in geom_bar(stat = "identity", fill = barfill, color = barcolor, :
## Ignoring empty aesthetic: `width`.
#Calculate the loading The first principal component is driven almost entirely by indicators of institutional trust, including trust in politicians, parliament, political parties, the legal system, the police, and supranational institutions. This suggests that PC1 captures a general level of institutional trust. In contrast, social trust variables load much more weakly on this component, indicating that they are not central to the structure of the first principal component.
The second principal component is mainly shaped by social trust variables, namely perceptions of whether other people can be trusted, are fair, and are willing to help. Institutional trust variables contribute much less to this dimension and tend to load in the opposite direction. This pattern indicates that PC2 primarily reflects differences in social trust rather than variations in institutional trust.
#pca1
loading_PC1 <- pca_trust$rotation[, 1]
abs_loading_PC1 <- abs(loading_PC1)
PC1_ranked_vars <- names(sort(abs_loading_PC1, decreasing = TRUE))
pca_trust$rotation[PC1_ranked_vars, 1]## trstplt trstprl trstprt trstlgl trstep trstun trstplc
## -0.3682793 -0.3620772 -0.3564590 -0.3490527 -0.3327059 -0.3298992 -0.3213053
## ppltrst pplfair pplhlp
## -0.2559769 -0.2441078 -0.1910316#pca2
loading_PC2 <- pca_trust$rotation[, 2]
abs_loading_PC2 <- abs(loading_PC2)
PC2_ranked_vars <- names(sort(abs_loading_PC2, decreasing = TRUE))
pca_trust$rotation[PC2_ranked_vars, 2]## pplhlp ppltrst pplfair trstep trstun trstplt
## 0.54292979 0.51470034 0.50581135 -0.21616121 -0.21565587 -0.19970857
## trstprt trstprl trstlgl trstplc
## -0.17185060 -0.11872884 -0.08325497 -0.02807990fviz_pca_var(pca_trust, col.var="steelblue")## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## ℹ The deprecated feature was likely used in the ggpubr package.
## Please report the issue at <https://github.com/kassambara/ggpubr/issues>.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## ℹ The deprecated feature was likely used in the factoextra package.
## Please report the issue at <https://github.com/kassambara/factoextra/issues>.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Individual-level PCA results
The individual-level PCA scores show clear variation across respondents on the first two components. The first principal component (PC1) mainly reflects overall institutional trust, and individuals are widely dispersed along this dimension. This indicates substantial differences in trust toward political and public institutions across Europe, not only between countries but also within countries.
The second principal component (PC2) captures social trust, including views on whether other people can be trusted, are fair, and are willing to help. Individuals also show clear positive and negative variation along this dimension, suggesting that social trust does not simply mirror institutional trust but retains a certain degree of independence.
Overall, the distribution of individuals in the PCA space reinforces the earlier findings: trust in European societies is clearly multidimensional. Different forms of trust do not move in a single direction but combine in varied ways at the individual level.
ind<-get_pca_ind(pca_trust)
print(ind)## Principal Component Analysis Results for individuals
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the individuals"
## 2 "$cos2" "Cos2 for the individuals"
## 3 "$contrib" "contributions of the individuals"ind$coord## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## AT.2227 -4.88216394 0.02382098 -0.355398571 0.728905436 -0.23358878
## AT.526 0.72149499 1.07138904 2.055530546 -0.907847025 0.16622550
## AT.195 -0.50135273 1.89037206 0.892998616 0.387438481 0.49192302
## AT.1842 -4.03109799 0.13347137 -0.563238271 0.445054357 -0.61625795
## AT.1142 0.49851699 1.39100886 1.086668293 -0.793659740 -0.13532363
## BE.3677 -1.90174936 1.21802496 0.294849623 0.039360638 -0.33784624
## BE.3607 -0.20985220 0.48422414 1.071477869 -0.522981820 0.38945730
## BE.3622 -1.15285352 0.36998047 -0.416479016 -0.241265966 0.18426281
## BE.3392 -1.74312643 1.21963458 -0.085440830 0.499130893 0.01180513
## BE.3752 -0.13512569 0.53604171 -0.503847184 -0.238419141 0.05712211
## BG.4613 2.69729110 -2.08575803 -0.243643427 0.415840974 -0.42898545
## BG.5575 4.33576650 1.58562162 -0.967887109 0.044148469 -0.38067898
## BG.4959 0.17255159 -0.33335154 -0.871535304 0.820671614 0.14706988
## BG.5063 0.49646791 1.54770619 -0.814962147 -0.000558615 1.29486258
## BG.4901 1.80970938 0.59142385 1.604154252 -0.083395976 0.01336216
## CH.6535 -1.73817413 0.27873040 -1.805149219 -1.564980863 0.31396531
## CH.7204 -2.22755127 0.59427974 0.316701150 -0.869935402 -0.20941893
## CH.7566 -0.66987432 0.49741521 -1.039063000 -0.218570570 -0.10743757
## CH.7027 -1.40342772 -1.23400583 0.596526193 -0.288318585 -0.90299706
## CY.7997 0.40965757 -2.84748230 -0.307415947 0.533193897 -0.58930197
## CY.8220 -0.29700520 -0.69085736 0.171329980 -2.368311866 1.27268428
## CY.7782 -1.92236071 -0.62816513 -0.285099971 1.330518842 -0.18006642
## CY.8161 0.78943659 -0.02240388 1.076128871 0.477419146 1.03542765
## DE.8811 -1.85490317 -0.42288963 -0.098087546 -0.437229586 0.46921845
## DE.10151 0.29587586 -0.18868560 -0.651072659 0.211753860 0.06144753
## DE.8629 -0.33017959 0.29008960 0.235167143 -0.721969807 1.32651304
## DE.10055 -2.33845375 -0.47771227 -0.432543984 0.123433624 0.77319790
## EE.11581 -3.41490392 -0.26340294 -0.462219720 -1.035550512 0.15975327
## EE.11613 -2.58325062 -0.51106161 0.105360362 0.343555322 -0.33188444
## EE.11723 4.17817995 0.87228280 0.315724161 0.265756179 -0.63115645
## EE.11599 0.80006403 -0.08106115 1.124422427 -1.333837191 -0.09881549
## EE.11632 -2.70229396 1.38279200 -0.589267849 -0.503893881 -0.42499704
## ES.12278 -0.14099154 -0.18723199 -1.764868803 -0.694910358 0.54503042
## ES.13128 2.68069231 3.03527905 0.655455060 -0.119126251 -0.06950546
## ES.13217 -0.45700020 1.22002132 0.229992290 0.532296072 1.62909799
## ES.12135 -1.37025123 -0.97254033 0.416775558 -0.094342537 0.32129980
## ES.12186 1.47048297 0.07748053 -0.402787587 -2.324021271 0.84425001
## FI.15127 -3.03834606 -0.94869425 -0.081319139 -0.455137924 0.64859663
## FI.14394 -5.02661620 1.08179840 -0.434690347 0.529858585 -0.10078115
## FI.13885 -3.31464943 -0.08228206 -0.618284431 0.063047197 0.13415322
## FI.14401 -2.24595521 0.32753878 0.433206884 -0.744511933 0.56625846
## FI.13954 -0.47603976 0.24117198 0.944512816 -1.869734588 -1.04436173
## FR.16098 -3.63744032 -0.77134745 -0.373596205 0.475264445 -0.25355096
## FR.16235 1.71138346 1.08096942 -1.080250103 -1.188531265 0.88632724
## FR.15529 1.52420985 0.47403285 0.209797100 0.432558392 -0.27979971
## FR.15670 -1.42085502 -0.23822575 -0.016742943 -0.597304851 0.99466743
## FR.15653 -1.53063969 -0.68948345 -0.504348606 0.368434691 0.74723568
## GB.18634 -0.49691576 1.84218607 -0.162390631 -0.553311151 -0.44499038
## GB.17188 -0.56885297 1.06430931 1.271962273 0.485324695 0.11681168
## GB.17578 -1.99480678 -0.09995615 -0.227825003 1.050073303 0.03861553
## GB.17237 1.53585404 -0.24496206 -1.059498622 0.291117715 0.75397632
## GB.17463 0.73845513 1.45306911 -0.335035433 0.231439735 -0.43766950
## GR.21407 0.63497622 -3.09920020 -0.118315614 -0.998565662 -1.70157943
## GR.21335 1.43620834 -0.52840278 0.984725495 0.173467144 -0.30401207
## GR.21477 1.32998428 0.70704842 1.487863969 -0.808430212 -0.11339939
## GR.20014 0.31437896 0.28414426 1.901447239 -0.380473640 0.50849389
## GR.19583 0.26284298 0.85346246 0.982700435 -0.052587738 0.62397402
## HR.22821 -1.51652630 1.23679263 -0.552492867 0.795929081 -0.40461342
## HR.21962 1.29488962 0.77606250 -0.280235047 0.871210373 -0.43768265
## HR.21622 4.77225380 -1.30343209 0.127767013 -0.472667823 -0.62056912
## HR.22104 -0.17235254 1.18864496 -1.036825546 0.587799287 -0.11587121
## HR.21601 -1.67662455 0.17705813 -0.019928105 0.239354977 -1.11215632
## HU.25268 -0.44326149 -1.23794784 1.633074988 -0.159861904 0.51259034
## HU.25189 1.73417536 -2.87837660 1.293801115 0.577915447 0.12986831
## HU.25070 -0.51051774 -0.06211262 0.543675176 0.401109952 -0.27039829
## HU.23906 0.48083320 -0.37068438 1.549125374 0.448223479 1.02337847
## HU.24483 -2.74634571 0.18058840 -1.060424352 -0.454494786 -1.24464501
## IE.26197 -1.14742323 1.12986448 0.803725886 -0.309160416 -0.30388602
## IE.26275 -3.18553700 -5.69802899 0.214745694 0.261413474 -0.67750728
## IE.25806 -1.41806232 1.64598660 0.201022849 0.551862079 0.54550850
## IL.27577 3.47260321 -0.40617006 -0.763434186 0.050172340 -0.64363739
## IL.28166 4.55317022 1.14175664 -0.761112509 0.266614741 -0.57245834
## IL.27572 3.73973057 1.33825083 -0.407492428 1.024398101 -1.74809187
## IL.27957 -2.64404793 -3.33517308 1.104635016 -0.613256391 -1.10701575
## IS.28313 0.74915314 0.57058034 -1.844868808 -0.953666486 -0.95732431
## IS.28302 -2.04484757 0.14446317 -0.897893360 0.332069013 -0.09742773
## IS.28350 -1.02590930 -0.14328871 -0.145901147 0.106288416 1.17749159
## IS.28256 -1.67876393 1.28925220 0.563359777 0.439107508 0.61944950
## IS.28675 1.22334331 -1.44382042 -0.290486734 0.802239194 0.61114816
## IT.30968 1.92314079 -1.51726239 0.126298215 0.087517732 0.08912624
## IT.30535 -0.52136884 1.47090933 0.561032076 1.406216012 0.59763488
## IT.29514 1.25500659 0.49400209 0.412389983 -0.481057589 -0.50664214
## IT.31149 0.60082148 0.44149888 0.110537789 -0.408835197 -0.37360178
## IT.30948 -0.14328711 -1.89090163 -0.001386619 -0.133264078 0.33335664
## LT.33008 0.22493682 0.57931715 1.230308046 0.552947198 0.01122841
## LT.32064 -4.64546100 -0.18142686 -0.479097654 0.942302457 0.08159265
## LT.32974 -0.94285667 -1.05042380 -0.867758893 0.570759679 0.04131714
## LT.32997 0.05866712 -0.72126928 1.739857346 0.268748423 -0.43346030
## LV.33500 -1.90921500 0.07777179 0.806119986 1.452298934 -0.37635271
## LV.33874 3.82691349 0.47754712 -1.142299627 0.605881045 0.37932033
## LV.33594 2.18808232 1.36114718 0.838460559 0.828505816 0.66314763
## LV.33990 3.92195744 -0.62784855 -0.231688584 -0.500763662 -0.56187614
## LV.33391 -2.06309029 -0.10615352 -0.515265594 -0.172455576 1.07855319
## ME.35202 -0.71395712 -1.28571181 -1.129830367 0.749611339 -0.13727424
## ME.35330 0.52012057 0.65027690 0.096564272 0.189331445 -1.44138190
## ME.35850 2.19018005 1.02945211 0.857506997 -1.019789217 -0.73814565
## ME.35447 1.73784384 -1.02779463 0.135698535 0.145962342 0.15039349
## NL.37003 -2.79519949 -0.09833954 -0.209398852 0.447154140 -0.56905491
## NL.36368 -3.35113919 -0.41917011 -0.880881020 0.004459795 0.36156362
## NL.36972 -3.77461958 0.32115818 -0.190390661 0.331936847 -0.63312412
## NL.37262 0.42376738 0.40709660 -0.420148671 1.013648508 -0.28049893
## NL.37108 -1.36595705 0.95061171 0.684425606 0.095111056 -0.04993670
## NO.38439 -1.61142017 1.10219399 0.643935749 0.226986514 0.70389895
## NO.38297 -3.25283233 0.43069073 0.538801132 -0.174240213 -1.15830216
## NO.37971 -2.36198833 -0.72652106 -0.329355949 0.009531961 0.25592919
## NO.38486 -3.22476094 0.17386067 -0.107777536 -1.201611448 -0.51439070
## NO.38587 -0.53828247 -0.50581818 -0.136351359 0.700301837 0.68857671
## PL.39317 3.61988193 -0.61825937 0.703540256 -0.833839163 0.40089413
## PL.40572 0.58340130 0.11304065 -0.958073512 -1.999761953 1.52394957
## PL.39312 -1.68307313 -0.71907209 -0.800161703 -0.461101874 0.70694109
## PL.39583 -1.23867155 -0.18959871 1.419257547 -0.255789253 -0.97944879
## PL.40186 2.73564010 1.60430390 -1.231628204 1.105915914 -0.92891326
## PT.40925 2.46430881 -1.84006381 1.165729542 -1.267799684 0.39523137
## PT.41903 5.09395210 0.04766564 -0.190183704 0.659747878 -0.83743184
## PT.41388 -1.84337450 -0.13112157 -0.086047535 -0.276139042 -0.08007563
## PT.41861 2.72204403 1.05440088 -1.910741593 -0.564567214 1.04126212
## PT.41962 -1.63335950 -0.80174413 -1.872504446 -0.930406940 0.08507187
## RS.42957 4.67507952 -0.70520441 0.350342093 -1.226488007 0.43421343
## RS.42794 0.88890910 1.57023340 -0.012806013 0.069649669 0.47763497
## RS.42109 3.42900640 2.05485215 -0.372660732 0.748310875 -0.40380572
## SE.43990 0.50165166 0.26463398 -0.142388365 0.506517951 -0.57373960
## SE.44124 -3.57164002 0.28603918 0.049235504 -0.700440853 -1.16749474
## SE.44642 -1.35686768 -0.29993611 -0.547338504 0.117923966 -0.25688084
## SE.43574 -3.36513774 0.27566358 0.085620248 -0.017473442 -0.29010766
## SE.43731 -3.06806069 1.34014656 0.628876784 -0.355762797 -0.01204623
## SI.45445 3.90180401 0.37970437 1.422730910 -0.060947778 -0.25338127
## SI.45265 0.27073900 -0.23478248 1.114181382 0.394306887 0.12634531
## SI.45750 1.55191185 0.39763398 -0.135275208 0.767555826 0.08475769
## SI.45109 -0.25899711 -0.78700896 1.121256319 1.123001590 0.04105572
## SI.45224 0.42316991 1.35839373 0.312700668 0.896081552 -0.80792044
## SK.46957 3.73626783 0.46614555 -1.848255770 -0.789563172 -1.04143981
## SK.46885 5.74766592 -1.55704524 -0.356416499 0.078850714 -0.69875292
## SK.46208 3.45803193 -0.84019872 -1.021620608 -1.507679436 -1.00413911
## SK.47201 2.04126925 -2.15662011 0.105475131 1.205053293 0.16275636
## UA.48331 4.34430111 -1.35470022 -0.655429412 -0.110033468 0.69092609
## UA.49680 3.28748462 -1.89847378 -0.330944339 0.879685322 0.97142254
## UA.48009 3.05624035 -0.64486035 -0.228675985 1.262211603 1.14159944
## UA.49587 2.93506541 -2.25498441 -0.685110334 1.925837503 1.91508931
## Dim.6 Dim.7 Dim.8 Dim.9 Dim.10
## AT.2227 -0.525129492 -9.478556e-02 0.43362747 0.118999599 -0.201144151
## AT.526 1.022502030 -8.277619e-01 -0.64727342 -0.375600910 -0.361326716
## AT.195 -0.638649071 -2.120398e-01 -0.04464793 0.123223387 0.023449445
## AT.1842 0.322109218 -2.265952e-01 -0.26379930 -0.436101501 0.046301401
## AT.1142 -0.089956605 4.656909e-02 -0.05386433 0.325733432 0.144329718
## BE.3677 0.190213075 -3.582340e-01 -0.05158054 -0.311778104 -0.498572710
## BE.3607 0.342143039 1.306169e-01 0.81910191 0.267745294 0.366343093
## BE.3622 -0.198977732 -2.381299e-01 0.33431310 -0.132172424 0.018812246
## BE.3392 0.130904964 -1.674882e-01 -0.47962092 -0.120690240 0.725698352
## BE.3752 0.091559528 2.222544e-01 0.36326724 0.029487377 0.154919703
## BG.4613 0.530220662 -1.482693e-01 0.14360949 0.073415025 -0.059339908
## BG.5575 -0.291711641 2.139862e-01 -0.10178584 -0.291103230 -0.131225252
## BG.4959 -0.038201584 7.552106e-02 0.74419994 -0.320934093 -0.241509417
## BG.5063 -0.522659649 -9.915580e-02 -0.35366770 0.228332745 -0.282280449
## BG.4901 -0.275020013 -4.054561e-01 1.26967842 0.897138171 -0.229337789
## CH.6535 -0.581053995 1.137614e+00 -0.43543615 -0.571100011 -0.348532137
## CH.7204 -0.103004042 7.750565e-01 0.74941455 -0.386581847 -0.208086446
## CH.7566 -0.167592826 -1.108970e-01 0.06207104 -0.098361131 -0.051511273
## CH.7027 -0.500616907 4.021855e-01 -0.43023693 -0.571312108 -0.011476734
## CY.7997 -1.195102429 2.755558e-01 0.25655551 -0.112129218 0.164443499
## CY.8220 -0.262741009 5.332889e-01 0.69109780 -1.604113296 -0.002254569
## CY.7782 -0.017491688 1.987540e-01 -0.15254632 0.249230882 0.338083661
## CY.8161 -0.256842489 -1.426311e-01 -0.43584201 0.353649045 -0.546502598
## DE.8811 -0.056000086 -3.694631e-01 -0.02535903 -0.198451459 0.267669243
## DE.10151 1.007829087 5.804402e-01 0.42685343 -0.462224847 -0.193561508
## DE.8629 -0.176922399 1.836366e+00 -0.47375421 0.575659108 -0.140790657
## DE.10055 0.483561141 1.729936e-01 -0.51109608 0.090683330 -0.264316504
## EE.11581 0.563495147 -5.201395e-01 0.24186031 0.628067816 -0.198591307
## EE.11613 1.367151203 1.660525e-01 -0.40193159 -0.401129817 -0.156190142
## EE.11723 -0.321870450 -1.103835e-01 0.66968572 0.187156969 0.056812409
## EE.11599 -0.532229566 -1.979875e-01 -0.01501649 0.311320244 -0.143311571
## EE.11632 0.024139388 -2.906089e-01 -0.23096842 0.788520038 0.011895078
## ES.12278 0.964481822 1.075668e+00 0.08164882 -0.647902600 0.216826056
## ES.13128 0.383612814 -2.412030e-01 0.05403520 -0.247439264 -0.175670317
## ES.13217 -0.069250179 -3.157220e-02 0.60224182 0.007731247 0.228440053
## ES.12135 -0.451848671 1.038380e-01 -0.56764298 0.775870941 0.204697826
## ES.12186 0.087847298 1.199631e-01 -0.28054601 0.259717631 0.230472645
## FI.15127 0.513753986 -1.619631e-02 -0.23707826 0.197942510 -0.189177330
## FI.14394 -0.212789669 -1.953872e-01 0.17307796 0.247860530 0.029788860
## FI.13885 0.140219659 -3.051908e-02 -0.11745877 0.091070612 0.021650081
## FI.14401 -0.230791649 -1.981752e-02 -0.02739524 -0.177561352 0.118462348
## FI.13954 0.475872985 -1.353437e-01 0.48741583 0.453414081 0.216432036
## FR.16098 -0.210348404 -7.585695e-01 0.04883402 0.077994926 -0.183252801
## FR.16235 -0.939232598 -1.354997e+00 -1.20121114 -0.081213730 -0.240638306
## FR.15529 0.143426440 -1.209447e-01 0.05209742 -0.181292619 -0.420996938
## FR.15670 0.119316423 1.071857e+00 -0.13621764 0.020473921 -0.148101127
## FR.15653 0.691824461 -1.548308e+00 0.21466198 -0.348518162 0.148577575
## GB.18634 -0.237239948 -8.289104e-02 -0.09949584 -0.147447227 -0.083043072
## GB.17188 -0.433345432 -2.810040e-03 -0.03265568 -0.633298512 -0.069417023
## GB.17578 -0.864463581 -5.027194e-01 -0.52831172 -0.596653751 -0.051187375
## GB.17237 -0.383195267 4.686471e-02 -0.14692312 0.227268994 0.060290303
## GB.17463 -0.516713463 -1.859432e-01 -0.24843497 -0.328911924 -0.227001215
## GR.21407 0.359883977 1.290147e-01 -0.44869248 -0.019486370 -0.374372808
## GR.21335 0.232406002 -6.081995e-02 -0.34909480 -0.210065511 -0.422326092
## GR.21477 -0.692047553 2.322299e-01 -0.43809294 0.099895498 0.136646567
## GR.20014 -0.625037853 -3.786327e-01 -0.73533466 0.632799321 0.051708476
## GR.19583 -0.695286639 3.230454e-01 0.47737925 -1.138152514 -0.200870575
## HR.22821 0.016655984 -1.192353e-02 0.81405169 0.527530029 0.783987450
## HR.21962 0.123442726 1.273148e-01 1.04430389 -0.181432556 -1.437959468
## HR.21622 -0.459736929 -7.743287e-02 -0.20453644 -0.224396585 0.206043099
## HR.22104 -0.094247617 5.994133e-02 -0.06311064 -0.132703212 -0.106075701
## HR.21601 0.374428796 -4.798797e-01 0.97921021 -0.103892684 -0.058958885
## HU.25268 -0.502386858 9.297040e-01 -0.20592352 0.299711109 0.202362465
## HU.25189 -0.531574649 6.305305e-01 0.17750859 0.373981299 -0.183462899
## HU.25070 -0.081483247 -3.325952e-01 0.05529192 0.120702927 0.557825392
## HU.23906 0.912108396 -1.135255e+00 -0.06938488 -0.403842048 -0.648303200
## HU.24483 -0.121958001 -5.885432e-01 0.21200255 -0.279809280 0.050747764
## IE.26197 -0.181857118 -1.358641e-01 0.11998077 0.272183834 0.084987567
## IE.26275 -0.076101299 -5.367842e-01 0.13354471 -0.023924074 -0.014747501
## IE.25806 -0.212252847 3.219091e-02 0.27732868 -0.050613482 0.395689168
## IL.27577 -0.101396517 -1.828224e-01 0.12709733 -0.056199270 -0.130413306
## IL.28166 -0.273263693 2.659756e-01 -0.14614575 -0.313621103 -0.142555601
## IL.27572 -0.215372600 3.374870e-01 0.02776086 -0.481090959 0.062076403
## IL.27957 0.169852897 5.767441e-01 0.11907568 -0.599120498 -0.107194557
## IS.28313 0.008629501 2.869723e-01 -1.33568972 0.718822276 -0.133219997
## IS.28302 0.013651896 1.463969e-01 0.33513264 0.335836764 0.154842702
## IS.28350 -0.816258179 -6.504599e-02 0.12882384 0.085055195 -0.120899924
## IS.28256 0.048760460 1.912432e+00 1.27333020 1.306657342 -0.679605695
## IS.28675 -0.357905293 3.889110e-01 0.70306574 -0.435803393 0.225291784
## IT.30968 -0.693068647 3.559557e-02 -0.03775141 0.425023241 0.166211839
## IT.30535 0.906127605 -4.469554e-01 0.21428257 -0.609682196 0.950586496
## IT.29514 -0.436897824 -1.269750e-01 -0.49166981 -0.238167300 0.149808226
## IT.31149 0.083102633 -8.580614e-02 -0.32688112 0.509707378 0.011009321
## IT.30948 -0.010835371 -1.872422e-01 0.11290053 0.240700985 -0.190509380
## LT.33008 -0.229276078 -5.364327e-01 0.24896032 -0.609468255 -0.196258544
## LT.32064 0.277970752 5.195754e-02 -0.21258564 0.115811072 -0.010093035
## LT.32974 0.180091029 -5.130161e-01 0.79842828 0.101881779 0.001844628
## LT.32997 -0.966048861 -1.081777e+00 0.03691619 0.713545877 -0.076996823
## LV.33500 -0.147339787 1.875629e-01 -0.59219333 0.140227230 0.238300616
## LV.33874 1.139354495 -2.865771e-01 -0.75676201 0.797086563 -0.225860259
## LV.33594 0.221125571 -3.908011e-01 -0.47806519 -0.242642761 -0.267733863
## LV.33990 0.918731049 -3.439494e-01 0.66254558 -0.029532922 -0.055212042
## LV.33391 1.341879034 3.688838e-01 0.15557772 -0.828364982 -0.571930071
## ME.35202 -0.280251957 -4.694790e-01 0.23977268 -0.212594754 -0.169583540
## ME.35330 2.244512346 7.816967e-01 -0.15945425 -0.094037377 0.878417593
## ME.35850 -0.582013722 4.506493e-01 -0.47661479 0.171106474 0.123243945
## ME.35447 0.225770554 -5.026372e-02 -0.45677871 0.044686305 1.156116816
## NL.37003 -0.302126912 -2.767302e-01 0.02471670 -0.091859684 -0.109196319
## NL.36368 -0.653633839 -1.010539e-01 -0.25377174 -0.152196176 -0.016257958
## NL.36972 0.567474537 5.765793e-02 0.21816775 1.073348297 -0.699309994
## NL.37262 -0.208670512 5.108896e-01 -0.37333549 0.134111116 0.026634227
## NL.37108 0.351639695 7.279243e-01 -0.62516612 -0.439333356 0.033433413
## NO.38439 0.018392771 -5.721725e-01 0.10466630 -0.461109778 0.455374932
## NO.38297 0.074220520 -2.827208e-01 0.07242775 0.099648738 -0.374527984
## NO.37971 0.174180216 3.713425e-01 -0.41607482 -0.111464251 0.074241375
## NO.38486 -0.205244086 -6.948101e-01 -0.25827692 -0.085887162 0.118095050
## NO.38587 0.322685880 6.106303e-01 0.27969952 0.250246680 0.634161540
## PL.39317 -0.566332630 -5.907124e-01 0.31825910 -0.494409558 0.232613586
## PL.40572 0.925348271 -1.576007e-01 0.22314929 0.272724691 0.226961877
## PL.39312 0.650620251 -6.408337e-01 -0.10639236 -0.292407779 0.416318663
## PL.39583 -0.276063024 9.282353e-01 -1.00695511 0.339721124 0.204480647
## PL.40186 0.640431142 1.621509e-01 -1.06188109 0.219862580 -0.084528587
## PT.40925 0.611071203 -5.529198e-01 -0.12027667 -0.170264197 -0.059970263
## PT.41903 0.598271259 5.913459e-01 -0.44818972 -0.513291916 -0.188713210
## PT.41388 0.314889820 -2.033874e-01 0.25397251 0.868769975 -0.109683182
## PT.41861 -0.429786318 -1.425355e-01 0.09481917 0.075881161 0.020921565
## PT.41962 -0.246377781 1.894076e-01 0.06613583 0.515728670 -0.075907991
## RS.42957 1.155678839 -8.167541e-02 0.66030184 0.209668787 0.205578767
## RS.42794 -0.216370522 -2.994309e-01 0.39792096 -0.069217578 -0.001993557
## RS.42109 -0.191891366 -2.632783e-01 0.23772746 0.486911372 -0.084093916
## SE.43990 -0.734015025 -2.236787e-01 -0.09895351 -0.084350430 0.166737799
## SE.44124 0.284399063 -4.661248e-01 -0.61326225 0.236745485 -0.227605309
## SE.44642 0.011500360 -5.871414e-01 0.20681598 -0.209179186 0.427010978
## SE.43574 -0.515073385 5.752707e-05 0.18339262 -0.316383543 0.037349940
## SE.43731 -0.909727361 9.730894e-01 -0.02236772 -0.170377846 0.385623528
## SI.45445 1.284511913 -8.084343e-03 0.20410174 -0.127764998 -0.034961318
## SI.45265 0.086852768 2.697674e-01 -0.13986102 -0.684804144 -0.023180449
## SI.45750 -0.019652178 5.166766e-01 0.06417007 -0.302221353 0.066260376
## SI.45109 0.794164143 5.985621e-01 -0.87916175 0.102281814 0.015234327
## SI.45224 0.281579112 7.370748e-01 0.23533613 0.052277800 0.152125657
## SK.46957 -1.314131516 -3.551404e-01 0.49863824 -0.341619589 0.153911085
## SK.46885 -0.396316489 2.101182e-01 -0.14463323 -0.231116028 -0.071086706
## SK.46208 -0.452678212 3.808605e-02 0.86532211 0.139455576 0.208705660
## SK.47201 -0.246290849 5.857303e-01 0.71141385 -0.073393874 0.008237773
## UA.48331 1.088059620 -6.150244e-01 -0.27938131 1.156749867 -0.032186031
## UA.49680 -0.766860155 9.424231e-02 -0.12946265 0.631029391 0.206981869
## UA.48009 -0.045974209 -2.617206e-01 0.76345037 0.737892885 0.229577650
## UA.49587 -0.248533416 1.522827e-02 -1.38426251 -0.518396471 -0.312022342Individual Contributions
This individual PCA plot focuses on how respondents are differentiated by the first two principal components. Most points are clustered near the center of the figure, indicating that the majority of respondents display trust levels close to the overall average and do not hold particularly extreme attitudes. The first principal component (horizontal axis) accounts for the main source of variation, with the clearest differences appearing between individuals located on the left and right sides of the plot. In contrast, the second principal component (vertical axis) plays a more limited role and only helps distinguish a subset of respondents.
The color of the points represents how well the first two principal components explain each individual (cos²). Points farther from the origin and shown in darker colors are better captured by the PCA and contribute more clearly to the overall structure, while points near the center with lighter colors reflect more moderate trust profiles that are not strongly differentiated by the first two components. Overall, the sample does not break into clearly separated groups but instead forms a continuous distribution along the first principal component. This suggests that trust differences are better understood in terms of degree rather than distinct trust types.
ind$contrib## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## AT.2227 3.0504158879 2.819695e-04 1.301286e-01 6.533109e-01 0.0827628962
## AT.526 0.0666194403 5.703969e-01 4.353007e+00 1.013451e+00 0.0419109028
## AT.195 0.0321677811 1.775732e+00 8.215671e-01 1.845793e-01 0.3670506711
## AT.1842 2.0796059334 8.852358e-03 3.268329e-01 2.435587e-01 0.5760455161
## AT.1142 0.0318049164 9.614850e-01 1.216565e+00 7.745442e-01 0.0277765955
## BE.3677 0.4628506678 7.372166e-01 8.956588e-02 1.905030e-03 0.1731290292
## BE.3607 0.0056358752 1.165133e-01 1.182791e+00 3.363185e-01 0.2300654550
## BE.3622 0.1700914950 6.802058e-02 1.787013e-01 7.157636e-02 0.0514999829
## BE.3392 0.3888589607 7.391664e-01 7.520944e-03 3.063419e-01 0.0002113846
## BE.3752 0.0023367390 1.427841e-01 2.615406e-01 6.989719e-02 0.0049492590
## BG.4613 0.9310863801 2.161775e+00 6.115766e-02 2.126337e-01 0.2791366394
## BG.5575 2.4058364926 1.249343e+00 9.651412e-01 2.396673e-03 0.2198110465
## BG.4959 0.0038104151 5.521889e-02 7.825488e-01 8.281640e-01 0.0328079579
## BG.5063 0.0315439955 1.190309e+00 6.842524e-01 3.837096e-07 2.5431916254
## BG.4901 0.4191331487 1.738123e-01 2.651146e+00 8.552000e-03 0.0002708225
## CH.6535 0.3866525707 3.860570e-02 3.357126e+00 3.011588e+00 0.1495185450
## CH.7204 0.6350234362 1.754949e-01 1.033334e-01 9.305753e-01 0.0665217417
## CH.7566 0.0574276442 1.229478e-01 1.112308e+00 5.874364e-02 0.0175083038
## CH.7027 0.2520660966 7.566886e-01 3.666068e-01 1.022169e-01 1.2368140130
## CY.7997 0.0214771333 4.029070e+00 9.736307e-02 3.495810e-01 0.5267535957
## CY.8220 0.0112891812 2.371699e-01 3.024184e-02 6.896922e+00 2.4568185622
## CY.7782 0.4729378802 1.960787e-01 8.374055e-02 2.176805e+00 0.0491809783
## CY.8161 0.0797570050 2.494188e-04 1.193081e+00 2.802704e-01 1.6261898225
## DE.8811 0.4403285270 8.886624e-02 9.912180e-03 2.350697e-01 0.3339503360
## DE.10151 0.0112034915 1.769132e-02 4.367173e-01 5.513663e-02 0.0057271764
## DE.8629 0.0139519459 4.181644e-02 5.697637e-02 6.409373e-01 2.6690380701
## DE.10055 0.6998289555 1.134006e-01 1.927534e-01 1.873460e-02 0.9068032266
## EE.11581 1.4924208719 3.447656e-02 2.201093e-01 1.318621e+00 0.0387107208
## EE.11613 0.8540187828 1.297864e-01 1.143657e-02 1.451346e-01 0.1670727077
## EE.11723 2.2341309143 3.780919e-01 1.026968e-01 8.684489e-02 0.6042348467
## EE.11599 0.0819188468 3.265189e-03 1.302568e+00 2.187677e+00 0.0148109123
## EE.11632 0.9345434896 9.501594e-01 3.577395e-01 3.122164e-01 0.2739703377
## ES.12278 0.0025440194 1.741979e-02 3.208975e+00 5.937930e-01 0.4505813552
## ES.13128 0.9196620647 4.578044e+00 4.426162e-01 1.744988e-02 0.0073277326
## ES.13217 0.0267280398 7.396352e-01 5.449643e-02 3.484047e-01 4.0255584745
## ES.12135 0.2402894705 4.700001e-01 1.789559e-01 1.094442e-02 0.1565858972
## ES.12186 0.2767287853 2.983101e-03 1.671451e-01 6.641370e+00 1.0811199223
## FI.15127 1.1814322235 4.472345e-01 6.812821e-03 2.547203e-01 0.6380887593
## FI.14394 3.2335962255 5.815344e-01 1.946711e-01 3.452212e-01 0.0154060151
## FI.13885 1.4060784175 3.364287e-03 3.938384e-01 4.887751e-03 0.0272981950
## FI.14401 0.6455598615 5.330994e-02 1.933446e-01 6.815863e-01 0.4863636703
## FI.13954 0.0290015217 2.890257e-02 9.190882e-01 4.298703e+00 1.6543737245
## FR.16098 1.6932695179 2.956534e-01 1.437959e-01 2.777462e-01 0.0975129412
## FR.16235 0.3748253859 5.806435e-01 1.202237e+00 1.736996e+00 1.1915709849
## FR.15529 0.2973198207 1.116605e-01 4.534615e-02 2.300737e-01 0.1187479832
## FR.15670 0.2583651115 2.820072e-02 2.888052e-04 4.387020e-01 1.5006780113
## FR.15653 0.2998335856 2.362275e-01 2.620614e-01 1.669162e-01 0.8469288427
## GB.18634 0.0316009316 1.686358e+00 2.716836e-02 3.764578e-01 0.3003536909
## GB.17188 0.0414127814 5.628834e-01 1.666825e+00 2.896292e-01 0.0206968499
## GB.17578 0.5092558257 4.964800e-03 5.347419e-02 1.355866e+00 0.0022618083
## GB.17237 0.3018799211 2.981813e-02 1.156491e+00 1.042113e-01 0.8622776759
## GB.17463 0.0697882898 1.049193e+00 1.156440e-01 6.586480e-02 0.2905522856
## GR.21407 0.0515999481 4.772896e+00 1.442200e-02 1.226114e+00 4.3917355421
## GR.21335 0.2639789048 1.387436e-01 9.990146e-01 3.700087e-02 0.1401888176
## GR.21477 0.2263744220 2.484169e-01 2.280699e+00 8.036419e-01 0.0195053240
## GR.20014 0.0126485660 4.011996e-02 3.724861e+00 1.780027e-01 0.3921960332
## GR.19583 0.0088415236 3.619525e-01 9.949099e-01 3.400529e-03 0.5905609629
## HR.22821 0.2943297975 7.601101e-01 3.144813e-01 7.789799e-01 0.2483203345
## HR.21962 0.2145852355 2.992789e-01 8.090705e-02 9.333050e-01 0.2905697359
## HR.21622 2.9146163761 8.442276e-01 1.681818e-02 2.747196e-01 0.5841334128
## HR.22104 0.0038016288 7.020807e-01 1.107523e+00 4.248500e-01 0.0203649247
## HR.21601 0.3597542871 1.557810e-02 4.091414e-04 7.044699e-02 1.8761320144
## HU.25268 0.0251451563 7.615307e-01 2.747601e+00 3.142443e-02 0.3985405957
## HU.25189 0.3848755810 4.116973e+00 1.724553e+00 4.106824e-01 0.0255822111
## HU.25070 0.0333546206 1.917090e-03 3.045233e-01 1.978356e-01 0.1109020589
## HU.23906 0.0295885192 6.827966e-02 2.472376e+00 2.470397e-01 1.5885623850
## HU.24483 0.9652609735 1.620550e-02 1.158513e+00 2.540009e-01 2.3497557956
## IE.26197 0.1684929022 6.343595e-01 6.655143e-01 1.175291e-01 0.1400725921
## IE.26275 1.2986724960 1.613363e+01 4.751059e-02 8.402982e-02 0.6962410941
## IE.25806 0.2573504716 1.346280e+00 4.163248e-02 3.744886e-01 0.4513721579
## IL.27577 1.5432797656 8.197823e-02 6.004608e-01 3.095325e-03 0.6283682849
## IL.28166 2.6531518711 6.477834e-01 5.968142e-01 8.740692e-02 0.4970722329
## IL.27572 1.7898431192 8.899340e-01 1.710726e-01 1.290372e+00 4.6351119982
## IL.27957 0.8946908215 5.527382e+00 1.257127e+00 4.624467e-01 1.8588284937
## IS.28313 0.0718249849 1.617768e-01 3.506489e+00 1.118331e+00 1.3901123343
## IS.28302 0.5351262037 1.037044e-02 8.305982e-01 1.355920e-01 0.0143978255
## IS.28350 0.1346952461 1.020250e-02 2.193102e-02 1.389151e-02 2.1030391184
## IS.28256 0.3606729687 8.259590e-01 3.269739e-01 2.370933e-01 0.5820275475
## IS.28675 0.1915274563 1.035879e+00 8.693488e-02 7.913803e-01 0.5665323787
## IT.30968 0.4733217871 1.143942e+00 1.643372e-02 9.418237e-03 0.0120487760
## IT.30535 0.0347876012 1.075114e+00 3.242775e-01 2.431541e+00 0.5417558326
## IT.29514 0.2015702108 1.212664e-01 1.752095e-01 2.845586e-01 0.3893447703
## IT.31149 0.0461982201 9.685944e-02 1.258818e-02 2.055295e-01 0.2117140103
## IT.30948 0.0026275355 1.776727e+00 1.980869e-06 2.183754e-02 0.1685582276
## LT.33008 0.0064752338 1.667691e-01 1.559442e+00 3.759628e-01 0.0001912353
## LT.32064 2.7617983987 1.635633e-02 2.364773e-01 1.091838e+00 0.0100979639
## LT.32974 0.1137694585 5.482919e-01 7.757818e-01 4.005752e-01 0.0025893590
## LT.32997 0.0004404777 2.585102e-01 3.118665e+00 8.881153e-02 0.2849904937
## LV.33500 0.4664917995 3.005570e-03 6.694850e-01 2.593520e+00 0.2148433025
## LV.33874 1.8742677198 1.133223e-01 1.344316e+00 4.513903e-01 0.2182448280
## LV.33594 0.6127194294 9.206465e-01 7.242804e-01 8.440509e-01 0.6670404449
## LV.33990 1.9685211734 1.958811e-01 5.530326e-02 3.083494e-01 0.4788647916
## LV.33391 0.5447168437 5.599530e-03 2.735292e-01 3.657059e-02 1.7644723614
## ME.35202 0.0652346887 8.214290e-01 1.315128e+00 6.909551e-01 0.0285831330
## ME.35330 0.0346212221 2.101258e-01 9.606704e-03 4.407811e-02 3.1513007639
## ME.35850 0.6138948293 5.266172e-01 7.575596e-01 1.278787e+00 0.8264486108
## ME.35447 0.3865056366 5.249228e-01 1.897107e-02 2.619746e-02 0.0343075585
## NL.37003 0.9999077966 4.805505e-03 4.517416e-02 2.458623e-01 0.4911793185
## NL.36368 1.4372068195 8.730987e-02 7.994218e-01 2.445724e-05 0.1982901709
## NL.36972 1.8233948028 5.125317e-02 3.734502e-02 1.354841e-01 0.6080081989
## NL.37262 0.0229820824 8.235267e-02 1.818643e-01 1.263433e+00 0.1193422272
## NL.37108 0.2387857596 4.490442e-01 4.826074e-01 1.112345e-02 0.0037824349
## NO.38439 0.3323165154 6.036689e-01 4.271954e-01 6.335452e-02 0.7515404420
## NO.38297 1.3541216795 9.217514e-02 2.990876e-01 3.733140e-02 2.0350517417
## NO.37971 0.7139862221 2.622884e-01 1.117564e-01 1.117228e-04 0.0993508012
## NO.38486 1.3308508479 1.502054e-02 1.196735e-02 1.775438e+00 0.4013450827
## NO.38587 0.0370812875 1.271369e-01 1.915404e-02 6.030427e-01 0.7191779767
## PL.39317 1.6769617169 1.899434e-01 5.099403e-01 8.549527e-01 0.2437760910
## PL.40572 0.0435581195 6.349683e-03 9.456689e-01 4.917384e+00 3.5226777344
## PL.39312 0.3625269590 2.569376e-01 6.596248e-01 2.614395e-01 0.7580505526
## PL.39583 0.1963571247 1.786296e-02 2.075219e+00 8.045297e-02 1.4551078674
## PL.40186 0.9577502155 1.278957e+00 1.562790e+00 1.503910e+00 1.3088264193
## PT.40925 0.7771853345 1.682475e+00 1.400029e+00 1.976418e+00 0.2369379024
## PT.41903 3.3208101664 1.128999e-03 3.726388e-02 5.352215e-01 1.0637281781
## PT.41388 0.4348720428 8.543405e-03 7.628134e-03 9.376335e-02 0.0097259605
## PT.41861 0.9482538810 5.524516e-01 3.761364e+00 3.919303e-01 1.6445681143
## PT.41962 0.3414270330 3.194143e-01 3.612328e+00 1.064445e+00 0.0109775057
## RS.42957 2.7971280082 2.471228e-01 1.264521e-01 1.849712e+00 0.2859816894
## RS.42794 0.1011227887 1.225212e+00 1.689543e-04 5.965071e-03 0.3460381336
## RS.42109 1.5047727834 2.098186e+00 1.430766e-01 6.885597e-01 0.2473299252
## SE.43990 0.0322061528 3.479958e-02 2.088769e-02 3.154766e-01 0.4992997787
## SE.44124 1.6325620554 4.065686e-02 2.497458e-03 6.032821e-01 2.0674813061
## SE.44642 0.2356184698 4.470337e-02 3.086409e-01 1.709943e-02 0.1000910273
## SE.43574 1.4492390466 3.776083e-02 7.552564e-03 3.754347e-04 0.1276586128
## SE.43731 1.2046537283 8.924571e-01 4.074484e-01 1.556319e-01 0.0002201070
## SI.45445 1.9483421994 7.164303e-02 2.085389e+00 4.567655e-03 0.0973824626
## SI.45265 0.0093807158 2.739139e-02 1.278949e+00 1.911817e-01 0.0242130778
## SI.45750 0.3082254088 7.856873e-02 1.885289e-02 7.244317e-01 0.0108965727
## SI.45109 0.0085846813 3.077812e-01 1.295243e+00 1.550737e+00 0.0025566957
## SI.45224 0.0229173238 9.169256e-01 1.007393e-01 9.873533e-01 0.9900768743
## SK.46957 1.7865301013 1.079756e-01 3.519375e+00 7.665690e-01 1.6451294281
## SK.46885 4.2278285836 1.204717e+00 1.308751e-01 7.645199e-03 0.7405919718
## SK.46208 1.5303555205 3.507897e-01 1.075278e+00 2.795088e+00 1.5293943695
## SK.47201 0.5332549817 2.311160e+00 1.146150e-02 1.785624e+00 0.0401797890
## UA.48331 2.4153172015 9.119460e-01 4.425816e-01 1.488768e-02 0.7240939333
## UA.49680 1.3831261628 1.790985e+00 1.128370e-01 9.515513e-01 1.4313573533
## UA.48009 1.1953892489 2.066399e-01 5.387442e-02 1.959033e+00 1.9767839967
## UA.49587 1.1024779349 2.526794e+00 4.835735e-01 4.560545e+00 5.5630093233
## Dim.6 Dim.7 Dim.8 Dim.9 Dim.10
## AT.2227 6.240812e-01 2.461400e-02 0.5910507685 0.0530563863 2.918077e-01
## AT.526 2.366119e+00 1.877192e+00 1.3169423709 0.5285668761 9.416338e-01
## AT.195 9.230662e-01 1.231778e-01 0.0062660495 0.0568896103 3.965948e-03
## AT.1842 2.348089e-01 1.406692e-01 0.2187451780 0.7125606490 1.546216e-02
## AT.1142 1.831363e-02 5.941463e-03 0.0091199755 0.3975313118 1.502427e-01
## BE.3677 8.188211e-02 3.515861e-01 0.0083630166 0.3641982843 1.792829e+00
## BE.3607 2.649255e-01 4.674088e-02 2.1089539665 0.2685903244 9.679611e-01
## BE.3622 8.960190e-02 1.553551e-01 0.3513160574 0.0654528227 2.552485e-03
## BE.3392 3.878114e-02 7.685397e-02 0.7230818496 0.0545746517 3.798343e+00
## BE.3752 1.897210e-02 1.353315e-01 0.4148047217 0.0032577590 1.730993e-01
## BG.4613 6.362409e-01 6.022830e-02 0.0648272346 0.0201937314 2.539660e-02
## BG.5575 1.925821e-01 1.254496e-01 0.0325661128 0.3174978007 1.241986e-01
## BG.4959 3.302714e-03 1.562551e-02 1.7408865779 0.3859032011 4.206782e-01
## BG.5063 6.182245e-01 2.693607e-02 0.3931714857 0.1953363504 5.747030e-01
## BG.4901 1.711736e-01 4.503867e-01 5.0673242145 3.0155417268 3.793439e-01
## CH.6535 7.640843e-01 3.545583e+00 0.5959916561 1.2219994479 8.761280e-01
## CH.7204 2.401136e-02 1.645753e+00 1.7653688706 0.5599246492 3.122982e-01
## CH.7566 6.356516e-02 3.369281e-02 0.0121107019 0.0362488058 1.913756e-02
## CH.7027 5.671779e-01 4.431501e-01 0.5818440502 1.2229072756 9.499890e-04
## CY.7997 3.232351e+00 2.080257e-01 0.2068968578 0.0471068713 1.950362e-01
## CY.8220 1.562298e-01 7.791534e-01 1.5013095100 9.6408815957 3.666140e-05
## CY.7782 6.924234e-04 1.082255e-01 0.0731466903 0.2327289341 8.243853e-01
## CY.8161 1.492939e-01 5.573478e-02 0.5971031967 0.4685885267 2.154102e+00
## DE.8811 7.097178e-03 3.739729e-01 0.0020214201 0.1475554529 5.167480e-01
## DE.10151 2.298699e+00 9.230240e-01 0.5727284555 0.8004850888 2.702215e-01
## DE.8629 7.083925e-02 9.238815e+00 0.7055005976 1.2415877883 1.429649e-01
## DE.10055 5.291893e-01 8.198944e-02 0.8211004922 0.0308107019 5.038839e-01
## EE.11581 7.186024e-01 7.412036e-01 0.1838740508 1.4779500299 2.844477e-01
## EE.11613 4.230010e+00 7.554203e-02 0.5078032671 0.6028601311 1.759499e-01
## EE.11723 2.344609e-01 3.338155e-02 1.4097214123 0.1312377199 2.327921e-02
## EE.11599 6.410712e-01 1.073924e-01 0.0007088068 0.3631293859 1.481305e-01
## EE.11632 1.318745e-03 2.313746e-01 0.1676858597 2.3295505599 1.020508e-03
## ES.12278 2.105215e+00 3.169964e+00 0.0209551646 1.5727732611 3.390821e-01
## ES.13128 3.330385e-01 1.593908e-01 0.0091779303 0.2293949757 2.225762e-01
## ES.13217 1.085301e-02 2.730912e-03 1.1400739735 0.0002239473 3.763799e-01
## ES.12135 4.620557e-01 2.953998e-02 1.0128421340 2.2554107426 3.022097e-01
## ES.12186 1.746486e-02 3.942697e-02 0.2473998434 0.2527257759 3.831075e-01
## FI.15127 5.973360e-01 7.186711e-04 0.1766748304 0.1467995815 2.581191e-01
## FI.14394 1.024730e-01 1.045900e-01 0.0941618040 0.2301767329 6.400143e-03
## FI.13885 4.449653e-02 2.551766e-03 0.0433672748 0.0310744306 3.380656e-03
## FI.14401 1.205448e-01 1.075962e-03 0.0023590738 0.1181254721 1.012145e-01
## FI.13954 5.124959e-01 5.018498e-02 0.7467762028 0.7702588173 3.378508e-01
## FR.16098 1.001352e-01 1.576481e+00 0.0074961147 0.0227918393 2.422050e-01
## FR.16235 1.996432e+00 5.030077e+00 4.5355496153 0.0247118685 4.176490e-01
## FR.15529 4.655504e-02 4.007480e-02 0.0085314650 0.1231422027 1.278321e+00
## FR.15670 3.221875e-02 3.147543e+00 0.0583254263 0.0015705389 1.581971e-01
## FR.15653 1.083179e+00 6.567689e+00 0.1448443256 0.4550902205 1.592166e-01
## GB.18634 1.273749e-01 1.882405e-02 0.0311172418 0.0814554015 4.973804e-02
## GB.17188 4.249881e-01 2.163331e-05 0.0033520356 1.5026699707 3.475473e-02
## GB.17578 1.691226e+00 6.923874e-01 0.8773476197 1.3338021795 1.889764e-02
## GB.17237 3.323139e-01 6.017136e-03 0.0678533812 0.1935205331 2.621663e-02
## GB.17463 6.042377e-01 9.472364e-02 0.1940066788 0.4053273494 3.716535e-01
## GR.21407 2.931118e-01 4.560123e-02 0.6328325380 0.0014226844 1.010859e+00
## GR.21335 1.222371e-01 1.013421e-02 0.3830698521 0.1653317190 1.286405e+00
## GR.21477 1.083877e+00 1.477523e-01 0.6032866760 0.0373885396 1.346726e-01
## GR.20014 8.841398e-01 3.927662e-01 1.6996570059 1.5003019762 1.928437e-02
## GR.19583 1.094047e+00 2.859071e-01 0.7163384896 4.8534168803 2.910144e-01
## HR.22821 6.278398e-04 3.895003e-04 2.0830283322 1.0426559961 4.433024e+00
## HR.21962 3.448572e-02 4.440747e-02 3.4280331118 0.1233323794 1.491335e+01
## HR.21622 4.783294e-01 1.642664e-02 0.1315020785 0.1886597076 3.061950e-01
## HR.22104 2.010245e-02 9.843527e-03 0.0125197717 0.0659795791 8.115471e-02
## HR.21601 3.172830e-01 6.309032e-01 3.0139988366 0.0404405085 2.507151e-02
## HU.25268 5.711956e-01 2.368031e+00 0.1332917088 0.3365521381 2.953533e-01
## HU.25189 6.394945e-01 1.089206e+00 0.0990444126 0.5240182869 2.427607e-01
## HU.25070 1.502605e-02 3.030609e-01 0.0096098056 0.0545861260 2.244287e+00
## HU.23906 1.882787e+00 3.530894e+00 0.0151328557 0.6110401444 3.031365e+00
## HU.24483 3.366114e-02 9.489748e-01 0.1412776276 0.2933397390 1.857444e-02
## IE.26197 7.484605e-02 5.057172e-02 0.0452495766 0.2775692334 5.209460e-02
## IE.26275 1.310667e-02 7.894005e-01 0.0560589007 0.0021444550 1.568624e-03
## IE.25806 1.019566e-01 2.838994e-03 0.2417579539 0.0095979637 1.129250e+00
## IL.27577 2.326775e-02 9.157073e-02 0.0507766518 0.0118333584 1.226664e-01
## IL.28166 1.689943e-01 1.938124e-01 0.0671372589 0.3685167470 1.465718e-01
## IL.27572 1.049758e-01 3.120413e-01 0.0024224633 0.8671636457 2.779297e-02
## IL.27957 6.529113e-02 9.113060e-01 0.0445694601 1.3448536608 8.287573e-02
## IS.28313 1.685309e-04 2.256201e-01 5.6079274160 1.9359303427 1.280032e-01
## IS.28302 4.217880e-04 5.871673e-02 0.3530406164 0.4225743619 1.729272e-01
## IS.28350 1.507868e+00 1.159148e-02 0.0521655394 0.0271049345 1.054227e-01
## IS.28256 5.380763e-03 1.002005e+01 5.0965148474 6.3969078997 3.331163e+00
## IS.28675 2.898975e-01 4.143796e-01 1.5537569473 0.7115868037 3.660771e-01
## IT.30968 1.087078e+00 3.471282e-03 0.0044797883 0.6768182004 1.992534e-01
## IT.30535 1.858177e+00 5.473011e-01 0.1443327554 1.3926875652 6.517262e+00
## IT.29514 4.319844e-01 4.417069e-02 0.7598682466 0.2125254474 1.618651e-01
## IT.31149 1.562924e-02 2.017134e-02 0.3358697423 0.9733936572 8.741843e-04
## IT.30948 2.657026e-04 9.605174e-02 0.0400666654 0.2170712993 2.617668e-01
## LT.33008 1.189668e-01 7.883671e-01 0.1948280529 1.3917103330 2.778043e-01
## LT.32064 1.748664e-01 7.395969e-03 0.1420558272 0.0502512464 7.347261e-04
## LT.32974 7.339939e-02 7.210408e-01 2.0038400134 0.0388901584 2.454141e-05
## LT.32997 2.112061e+00 3.206073e+00 0.0042837588 1.9076138844 4.275900e-02
## LV.33500 4.913018e-02 9.638104e-02 1.1023467918 0.0736735134 4.095739e-01
## LV.33874 2.937826e+00 2.249992e-01 1.8001548467 2.3804422390 3.679269e-01
## LV.33594 1.106589e-01 4.184171e-01 0.7183985757 0.2205877298 5.169976e-01
## LV.33990 1.910227e+00 3.241060e-01 1.3798209673 0.0032678303 2.198617e-02
## LV.33391 4.075070e+00 3.728010e-01 0.0760827231 2.5709293064 2.359216e+00
## ME.35202 1.777484e-01 6.038517e-01 0.1807135038 0.1693369610 2.074194e-01
## ME.35330 1.140125e+01 1.674074e+00 0.0799214635 0.0331320023 5.565241e+00
## ME.35850 7.666105e-01 5.563850e-01 0.7140460818 0.1096931616 1.095502e-01
## ME.35447 1.153567e-01 6.921612e-03 0.6558475894 0.0074816185 9.640184e+00
## NL.37003 2.065794e-01 2.098027e-01 0.0019203131 0.0316152462 8.599989e-02
## NL.36368 9.668906e-01 2.797721e-02 0.2024313391 0.0867868952 1.906399e-03
## NL.36972 7.287877e-01 9.107852e-03 0.1496140289 4.3164629267 3.527129e+00
## NL.37262 9.854406e-02 7.150757e-01 0.4381166575 0.0673870157 5.116372e-03
## NL.37108 2.798363e-01 1.451678e+00 1.2285195849 0.7231610522 8.062010e-03
## NO.38439 7.656013e-04 8.969164e-01 0.0344353879 0.7966275748 1.495616e+00
## NO.38297 1.246684e-02 2.189845e-01 0.0164892616 0.0372040550 1.011697e+00
## NO.37971 6.866034e-02 3.777872e-01 0.5441693614 0.0465498063 3.975337e-02
## NO.38486 9.533439e-02 1.322605e+00 0.2096826091 0.0276377814 1.005878e-01
## NO.38587 2.356504e-01 1.021538e+00 0.2459091276 0.2346298814 2.900559e+00
## PL.39317 7.258576e-01 9.559827e-01 0.3183852098 0.9158416444 3.902582e-01
## PL.40572 1.937844e+00 6.804784e-02 0.1565244732 0.2786734469 3.715247e-01
## PL.39312 9.579954e-01 1.125094e+00 0.0355805068 0.3203498445 1.250068e+00
## PL.39583 1.724745e-01 2.360555e+00 3.1872155780 0.4324060658 3.015687e-01
## PL.40186 9.282248e-01 7.203381e-02 3.5444021542 0.1811128698 5.153344e-02
## PT.40925 8.450685e-01 8.375722e-01 0.0454730439 0.1086158834 2.593903e-02
## PT.41903 8.100365e-01 9.580344e-01 0.6314151530 0.9871326605 2.568541e-01
## PT.41388 2.244014e-01 1.133303e-01 0.2027517628 2.8278494099 8.676848e-02
## PT.41861 4.180358e-01 5.566008e-02 0.0282607364 0.0215732017 3.156968e-03
## PT.41962 1.373762e-01 9.828623e-02 0.0137488004 0.9965273476 4.155822e-02
## RS.42957 3.022613e+00 1.827598e-02 1.3704911385 0.1647078268 3.048165e-01
## RS.42794 1.059509e-01 2.456355e-01 0.4977197230 0.0179506209 2.866416e-05
## RS.42109 8.333341e-02 1.899014e-01 0.1776437395 0.8882730942 5.100480e-02
## SE.43990 1.219321e+00 1.370715e-01 0.0307789368 0.0266576139 2.005165e-01
## SE.44124 1.830478e-01 5.952542e-01 1.1821801924 0.2099955465 3.736342e-01
## SE.44642 2.993168e-04 9.444597e-01 0.1344495717 0.1639395017 1.315104e+00
## SE.43574 6.004081e-01 9.066558e-09 0.1057194534 0.3750372808 1.006148e-02
## SE.43731 1.872970e+00 2.594200e+00 0.0015726596 0.1087609318 1.072529e+00
## SI.45445 3.734088e+00 1.790554e-04 0.1309437060 0.0611604193 8.815714e-03
## SI.45265 1.707165e-02 1.993778e-01 0.0614871852 1.7570310334 3.875481e-03
## SI.45750 8.740367e-04 7.313673e-01 0.0129436327 0.3422133623 3.166574e-02
## SI.45109 1.427345e+00 9.815588e-01 2.4295664799 0.0391961595 1.673896e-03
## SI.45224 1.794358e-01 1.488405e+00 0.1740878354 0.0102395596 1.669117e-01
## SK.46957 3.908283e+00 3.455399e-01 0.7815601150 0.4372524011 1.708526e-01
## SK.46885 3.554615e-01 1.209554e-01 0.0657547877 0.2001275142 3.644674e-02
## SK.46208 4.637538e-01 3.974017e-03 2.3536767510 0.0728649114 3.141596e-01
## SK.47201 1.372792e-01 9.399251e-01 1.5908742259 0.0201820971 4.894424e-04
## UA.48331 2.679253e+00 1.036293e+00 0.2453499181 5.0133218730 7.471654e-03
## UA.49680 1.330885e+00 2.433267e-02 0.0526841798 1.4919210691 3.089915e-01
## UA.48009 4.783401e-03 1.876609e-01 1.8321154756 2.0400147956 3.801378e-01
## UA.49587 1.397906e-01 6.353298e-04 6.0232117831 1.0068638401 7.021878e-01fviz_pca_ind(pca_trust, col.ind="cos2", geom="point", gradient.cols=c("white", "#2E9FDF", "#FC4E07" ))
In summary
Overall, this set of trust variables does not divide the sample into clearly distinct “types” of trust. Both the PCA results and the individual distribution plots show that most respondents are spread along a continuous axis: some are generally more trusting, while others are generally less trusting. Clear cases in which institutional trust and social trust move in opposite directions are relatively rare. In other words, the differences observed here are mainly about how much people trust, rather than what kind of trust pattern they belong to.
Placed in a broader comparative context, this stands in contrast to common intuitions about East Asian societies. In East Asian settings, people often draw sharper distinctions between different objects of trust. For example, trust in the state or formal institutions may remain relatively stable and abstract, while trust in individuals or strangers tends to be lower in everyday interactions. From a Chinese perspective, this contrast is familiar: institutions are often perceived as macro-level and broadly legitimate, whereas people are concrete actors who call for greater caution, leading to trust that does not move in sync across levels.
By comparison, the European context reflected in this sample shows much less separation between institutional and social trust. Instead, they tend to rise and fall together, forming a general assessment of whether the social system as a whole is reliable. From an overall perspective, trust in Europe appears more like a broad social mindset than a finely layered configuration directed at different objects. This implies that, when interpreting trust differences in European societies, it is more informative to focus on overall trust levels shaped by social context and personal experience, rather than on rigid trust categories.