Figure 5. Words related to appreciation
sel.apprec <-which(rownames(as.data.frame(res.mfact.23$freq.sup))
%in%c("agréable","agressif","asséchant","beau","bon","chaleureux","complexe","curieux","cos",
"défaut","dens","desequilibri","équilibré","généreux","onctueux","particulier",
"puissant","rond","souple","structuré","complex","velouté","gouleyant",
"malaqualitat","pinassa","potencia","rodó","secant","limite","plat","mou"))
sel.apprec
[1] 5 13 17 20 28 30 37 39 49 69 70 81 88 97 98 102 109 115 119
[20] 120 133 159 163 165 166 190 204 214 216plot.MFA(res.mfact.23,choix=c("freq"),invisible=c("row","col"),axes=c(1,2),select=sel.apprec ,unselect=1,
legend=list(plot=FALSE),habillage="none",autoLab = c("yes"),cex=0.8,
title="",graph.type="classic")
French translation of 22 words
df.apprec.Fr <- data.frame(orig= "agréable", transl="pleasant")
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "agressif", transl="aggressive") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "asséchant", transl="drying") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "beau", transl="beautiful") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "bon", transl="good") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "chaleureux", transl="warm") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "complexe", transl="complex") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "curieux", transl="curious") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "défaut", transl="defect") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "équilibré", transl="balanced") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "généreux", transl="generous") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "gouleyant", transl="tasteful") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "limite", transl="limit") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "mou", transl="soft") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "onctueux", transl="unctuous") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "particulier", transl="particular") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "plat", transl="flat") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "puissant", transl="powerful") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "rond", transl="round") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "souple", transl="supple") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "structuré", transl="structured") )
df.apprec.Fr <- rbind(df.apprec.Fr, data.frame(orig= "velouté", transl="velvet") )
df.apprec.Fr$lang <- "Fr"
Catalan translation of 8 words
df.apprec.Cat <- data.frame(orig= "complex", transl="high")
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "cos", transl="full_bodied") )
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "dens", transl="dense") )
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "desequilibri", transl="imbalance") )
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "malaqualitat", transl="poorquality") )
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "pinassa", transl="pinassa") )
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "rodó", transl="round") )
df.apprec.Cat <- rbind(df.apprec.Cat, data.frame(orig= "secant", transl="drying") )
df.apprec.Cat$lang <- "Cat"
To join French coordinates and their translation:
df.apprec.Fr
orig transl lang
1 agréable pleasant Fr
2 agressif aggressive Fr
3 asséchant drying Fr
4 beau beautiful Fr
5 bon good Fr
6 chaleureux warm Fr
7 complexe complex Fr
8 curieux curious Fr
9 défaut defect Fr
10 équilibré balanced Fr
11 généreux generous Fr
12 gouleyant tasteful Fr
13 limite limit Fr
14 mou soft Fr
15 onctueux unctuous Fr
16 particulier particular Fr
17 plat flat Fr
18 puissant powerful Fr
19 rond round Fr
20 souple supple Fr
21 structuré structured Fr
22 velouté velvet FrCoord.Fr.Fig5 <- merge(res.mfact.23$freq.sup$coord[1:135,], df.apprec.Fr, by.x=0, by.y="orig")
Coord.Fr.Fig5[,c(1:5,9,10)]
Row.names Dim.1 Dim.2 Dim.3 Dim.4 transl lang
1 agréable -0.3622113 -0.754415703 -0.03913020 -0.18872073 pleasant Fr
2 asséchant -0.6733810 -0.803561875 -0.10146317 0.27194795 drying Fr
3 beau 0.1846424 0.693693657 -0.09449363 -0.34464145 beautiful Fr
4 bon -0.3661349 0.786808717 0.47009306 0.30805796 good Fr
5 chaleureux 0.6657340 0.554044958 0.10360208 -0.21357552 warm Fr
6 complexe 0.5960483 0.507511318 0.86628447 0.57018982 complex Fr
7 curieux -0.3052359 -1.593741775 0.60169221 -0.23240807 curious Fr
8 défaut -0.5966568 -0.571192552 -0.15997103 -0.21422006 defect Fr
9 équilibré -0.2666819 0.078640165 0.40186324 0.52297614 balanced Fr
10 généreux 1.5848955 -0.002238351 -0.54439416 0.38322473 generous Fr
11 gouleyant -0.1072808 1.406847717 1.91993029 0.58127433 tasteful Fr
12 limite -0.3052359 -1.593741775 0.60169221 -0.23240807 limit Fr
13 mou -0.7423672 -0.059917941 -0.54080265 -0.20512605 soft Fr
14 onctueux 0.2819501 0.455975637 -0.76596827 -0.65328005 unctuous Fr
15 particulier -0.3052359 -1.593741775 0.60169221 -0.23240807 particular Fr
16 plat -0.7423672 -0.059917941 -0.54080265 -0.20512605 flat Fr
17 puissant 0.2324995 0.244534689 0.06489716 0.28386548 powerful Fr
18 rond -0.5120008 0.979784095 0.58862337 0.08993399 round Fr
19 souple -0.0343926 0.902010962 0.32855234 -0.57750861 supple Fr
20 structuré -0.1072808 1.406847717 1.91993029 0.58127433 structured Fr
21 velouté -0.0738231 -0.198647063 0.25657926 -0.24860346 velvet Fr
To join Catalan coordinates and their translation:
df.apprec.Cat
orig transl lang
1 complex high Cat
2 cos full_bodied Cat
3 dens dense Cat
4 desequilibri imbalance Cat
5 malaqualitat poorquality Cat
6 pinassa pinassa Cat
7 rodó round Cat
8 secant drying CatCoord.Cat.Fig5 <- merge(res.mfact.23$freq.sup$coord[136:nrow(res.mfact.23$freq.sup$coord), ], df.apprec.Cat, by.x=0, by.y="orig")
Coord.Cat.Fig5[,c(1:5,9,10)]
Row.names Dim.1 Dim.2 Dim.3 Dim.4 transl lang
1 complex 0.25621245 0.22501723 1.2599178 0.30005544 high Cat
2 cos 0.86235771 -0.09456111 0.4304749 0.27162192 full_bodied Cat
3 dens 0.37408790 -0.18174291 0.9994396 0.21541158 dense Cat
4 desequilibri -1.42400036 0.33008205 -0.9472114 1.37192587 imbalance Cat
5 malaqualitat -0.29536903 -1.55529185 0.7231142 -0.25969536 poorquality Cat
6 pinassa -0.84676461 -0.31271027 -0.4607370 0.43321992 pinassa Cat
7 rodó 0.02363637 -0.46725895 0.6915393 -0.35041152 round Cat
8 secant -0.53676643 -0.94764429 0.1811539 0.05678312 drying Cat
To join French and Catalan coordinates:
Coord.Fig5 <- rbind(Coord.Fr.Fig5, Coord.Cat.Fig5)
Coord.Fig5[,c(1:5,9,10)]
Row.names Dim.1 Dim.2 Dim.3 Dim.4 transl lang
1 agréable -0.36221131 -0.754415703 -0.03913020 -0.18872073 pleasant Fr
2 asséchant -0.67338104 -0.803561875 -0.10146317 0.27194795 drying Fr
3 beau 0.18464237 0.693693657 -0.09449363 -0.34464145 beautiful Fr
4 bon -0.36613490 0.786808717 0.47009306 0.30805796 good Fr
5 chaleureux 0.66573397 0.554044958 0.10360208 -0.21357552 warm Fr
6 complexe 0.59604830 0.507511318 0.86628447 0.57018982 complex Fr
7 curieux -0.30523593 -1.593741775 0.60169221 -0.23240807 curious Fr
8 défaut -0.59665679 -0.571192552 -0.15997103 -0.21422006 defect Fr
9 équilibré -0.26668190 0.078640165 0.40186324 0.52297614 balanced Fr
10 généreux 1.58489551 -0.002238351 -0.54439416 0.38322473 generous Fr
11 gouleyant -0.10728079 1.406847717 1.91993029 0.58127433 tasteful Fr
12 limite -0.30523593 -1.593741775 0.60169221 -0.23240807 limit Fr
13 mou -0.74236722 -0.059917941 -0.54080265 -0.20512605 soft Fr
14 onctueux 0.28195009 0.455975637 -0.76596827 -0.65328005 unctuous Fr
15 particulier -0.30523593 -1.593741775 0.60169221 -0.23240807 particular Fr
16 plat -0.74236722 -0.059917941 -0.54080265 -0.20512605 flat Fr
17 puissant 0.23249948 0.244534689 0.06489716 0.28386548 powerful Fr
18 rond -0.51200080 0.979784095 0.58862337 0.08993399 round Fr
19 souple -0.03439260 0.902010962 0.32855234 -0.57750861 supple Fr
20 structuré -0.10728079 1.406847717 1.91993029 0.58127433 structured Fr
21 velouté -0.07382310 -0.198647063 0.25657926 -0.24860346 velvet Fr
22 complex 0.25621245 0.225017231 1.25991777 0.30005544 high Cat
23 cos 0.86235771 -0.094561115 0.43047490 0.27162192 full_bodied Cat
24 dens 0.37408790 -0.181742905 0.99943959 0.21541158 dense Cat
25 desequilibri -1.42400036 0.330082052 -0.94721141 1.37192587 imbalance Cat
26 malaqualitat -0.29536903 -1.555291851 0.72311423 -0.25969536 poorquality Cat
27 pinassa -0.84676461 -0.312710270 -0.46073696 0.43321992 pinassa Cat
28 rodó 0.02363637 -0.467258947 0.69153926 -0.35041152 round Cat
29 secant -0.53676643 -0.947644286 0.18115389 0.05678312 drying CatCoord.Fig5$lang <- as.factor(Coord.Fig5$lang )
set.seed(1234)
Figure5 <- ggplot(Coord.Fig5)+
theme_light() + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
xlab(labx)+ ylab(laby) + coord_fixed()+
geom_hline(yintercept=0, linetype="dashed", color = "grey")+
geom_vline(xintercept=0, linetype="dashed", color = "grey")+
geom_text_repel(size=5, fontface = font.type.FRCat[Coord.Fig5$lang], max.overlaps=100,
box.padding = unit(0.35, "lines"),
aes(x=Dim.1, y=Dim.2, label = transl, color=lang))+
theme( axis.text.x = element_text(size=rel(1.6)))+
theme( axis.text.y = element_text(size=rel(1.6)))+
labs(x=labx)+labs(y=laby)+
theme(axis.title.x= element_text(size=17, face="bold"))+
theme(axis.title.y= element_text(size=17, face="bold"))+
theme(plot.margin = grid::unit(c(t=5,r= 2,b=5, l=2), "mm"))+
scale_color_manual(name="Language",
labels=c("Catalan","French"),
values = setNames(col.margin, levels(Coord.Fig4$lang))) +
theme(axis.title.x = element_text(margin=margin(t=10))) +
theme(panel.border = element_rect(colour = "black", fill=NA, linewidth=1)) +
theme(legend.position = "none")+
labs(title = "Words originally in <b style='color:#FF0000'>**_French_**</b> and **Catalan**")+
theme(plot.title = element_markdown(lineheight = 1.1, hjust=1, size=20))+
ylim(-1.9, 1.1)+
ggtitle("Figure 5. Words related to appreciation")
To plot Figure 5:
set.seed(1234)
Figure5
