Paper: Do Concepts Matter? [Script]
Felipe Rocha, Rodrigo Albuquerque, Marcelo de Almeida Medeiros
Info
This document aims to show all commands used to generate the results and figures exhibited at the paper entitled: “Do Concepts Matter? Latin America and South America in the Discourse of Brazilian Foreign Policymakers”
Packages
require(tidyverse)## Loading required package: tidyverse## ── Attaching packages ────────────────────────────────── tidyverse 1.2.1 ──## ✔ ggplot2 3.0.0.9000 ✔ purrr 0.2.4
## ✔ tibble 1.4.2 ✔ dplyr 0.7.5
## ✔ tidyr 0.8.1 ✔ stringr 1.3.1
## ✔ readr 1.1.1 ✔ forcats 0.3.0## ── Conflicts ───────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()Database
As explained at the methodological section of the paper, the database [or Corpus] was provided by Itamaraty, and it is available on its official website. However, we had to convert and change some features on some documents, as explained in the paper. This is exactly the reason why we created a folder called “corpus.rar” in which all data are also available. The number of speeches is an approximation based on the manual counting of the original summary as presented in the first pages of each document. The number of frequencies to Latin America and to South America were made through queries based on the expressions showed at the methodological appendix. For more information, please consult the codebook and other files available on this replication folder. Having said that, here follows the database:
database <- read.csv("dataframe_paper_do_concepts_matter.csv")
database## year resenha.pe latin.america south.america latin.minus.south president
## 1 1995 77 113 84 29 1
## 2 1996 140 170 107 63 1
## 3 1997 48 59 40 19 1
## 4 1998 64 42 21 21 1
## 5 1999 54 73 62 11 2
## 6 2000 245 197 458 -261 2
## 7 2001 264 158 134 24 2
## 8 2002 337 148 142 6 2
## 9 2003 276 129 458 -329 3
## 10 2004 575 200 424 -224 3
## 11 2005 565 201 897 -696 3
## 12 2006 640 233 667 -434 3
## 13 2007 707 301 415 -114 4
## 14 2008 361 161 226 -65 4
## 15 2009 437 213 314 -101 4
## 16 2010 602 296 292 4 4
## 17 2011 384 174 210 -36 5
## 18 2012 293 95 222 -127 5
## 19 2013 323 148 202 -54 5
## 20 2014 131 111 93 18 5
## perc.latin.america perc.south.america perc.latin.minus.south
## 1 0.80 0.60 0.20
## 2 1.11 0.68 0.43
## 3 1.07 0.71 0.36
## 4 0.76 0.31 0.45
## 5 0.95 0.74 0.21
## 6 1.41 3.28 -1.87
## 7 0.86 0.72 0.14
## 8 0.71 0.71 0.00
## 9 0.51 1.98 -1.47
## 10 0.62 1.31 -0.69
## 11 0.63 3.09 -2.46
## 12 0.75 2.08 -1.33
## 13 0.79 1.11 -0.32
## 14 1.13 1.73 -0.60
## 15 0.92 1.43 -0.51
## 16 1.06 1.06 0.00
## 17 0.89 1.13 -0.24
## 18 0.57 1.12 -0.55
## 19 0.65 1.02 -0.37
## 20 0.67 0.53 0.14Graph 01. Frequency of discourses per year
ggplot(database, aes(x=year, y=resenha.pe)) + geom_line() + geom_point(shape=21, fill="white", size=4) + scale_x_continuous(breaks = database$year) + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), axis.text.x = element_text(colour = "black", size = rel(1.4)), axis.text.y = element_text(colour = "black", size=rel(1.4)))
Graph 02. Frequency of use of the terms Latin America and South America per year
g2 <- database %>% select(year, perc.latin.america, perc.south.america) %>% gather(key = conceitos, value = valores, -year)
ggplot(g2, aes(x=year, y=valores, fill=conceitos)) + geom_line(position = position_dodge(0.4)) + geom_point(shape=21, size=4, position = position_dodge(0.4)) +scale_fill_manual(values = c("black", "white"), label=c("Latin America", "South America")) + guides(fill=guide_legend(title = NULL)) + theme(axis.title.x = element_blank(), axis.text.x = element_text(colour = "black", size = rel(1.5)), axis.text.y = element_text(colour = "black", size = rel(1.5)), legend.text = element_text(size=12), axis.title.y = element_text(size = rel(1.4))) + scale_x_continuous(breaks = g2$year) + ylab("%")
Graph 03. Annual Dominance
ggplot(database, aes(x=year, y=perc.latin.minus.south)) + geom_line() + geom_point(shape=21, size=4, fill="white") + scale_x_continuous(breaks = database$year) + geom_hline(yintercept = 0) + theme(axis.title.x = element_blank(), axis.text.x = element_text(colour = "black", size = rel(1.4)), axis.text.y = element_text(colour = "black", size = rel(1.4)), axis.title.y = element_text(size=rel(1.4))) + ylab("%")
Graph 04. Latin America and South America by presidential terms (mean)
g4 <- database %>% select(president, perc.latin.america, perc.south.america)
g4$president <- factor(g4$president, levels = c(1,2,3,4,5), labels = c("FHC1", "FHC2", "LULA1", "LULA2", "DILMA"))
g4 <- gather(g4, key = "conceitos", value = "valores", -president)
ggplot(g4, aes(x=president, y=valores, fill=conceitos)) + geom_bar(position="dodge", stat="summary", fun.y="mean", colour="black") +scale_fill_manual(values = c("white", "grey22"), label=c("Latin America", "South America")) + theme(axis.title.x = element_blank(), axis.text.x = element_text(colour = "black", size=rel(1.5)), axis.title.y = element_text(size = rel(1.4), colour = "black"), axis.text.y = element_text(size = rel(1.4), colour = "black")) + ylab("%") + guides(fill=guide_legend(title = NULL))
Graph 05. Conceptual dominance by presidential terms (mean)
g5 <- database %>% select(president, perc.latin.minus.south)
g5$president <- factor(g5$president, levels = c(1,2,3,4,5), labels = c("FHC1", "FHC2", "LULA1", "LULA2", "DILMA"))
ggplot(g5, aes(x=president, y=perc.latin.minus.south)) + geom_bar(position="dodge", stat="summary", fun.y="mean", fill="white", colour="black") + theme(axis.title.x = element_blank(), axis.text.x = element_text(colour = "black", size=rel(1.5)), axis.title.y = element_text(size = rel(1.4), colour = "black"), axis.text.y = element_text(size = rel(1.4), colour = "black")) + ylab("%") + guides(fill=guide_legend(title = NULL)) + geom_hline(yintercept = 0, colour="black", size=.9) 
Graph 06. An indicative association between concepts and events
ggplot(database, aes(x=year, y=perc.latin.minus.south)) + geom_line() + geom_point(shape=21, size=4, fill="white") + scale_x_continuous(breaks = database$year) + geom_hline(yintercept = 0) + theme(axis.title.x = element_blank(), axis.title.y = element_text(size = rel(1.4)), axis.text.x = element_text(colour = "black", size = rel(1.4)), axis.text.y = element_text(colour = "black", size = rel(1.4))) + annotate("text", label="I South American \n Summit", x=2000, y=-2.1) + annotate("text", label= "II South American \n Summit", x=2003, y=0.2) + annotate("text", label="Sub-secretary \n of South America", x=2003, y=-1.66) + annotate("text", label="SACN", x=2004, y=-0.5) + annotate("text", label="I SACN Summit", x=2005, y=-2.6) + annotate("text", label="II SACN \n Summit", x=2007, y=-1.4) + annotate("text", label="UNASUR\nCALC", x=2008, y=-0.8) + annotate("text", label="CELAC", x=2010, y=0.2) + ylab("%")