---
title: "GDELT Events: Poland"
author: Gagan Atreya
date: today
format:
html:
toc: true
toc-location: left
toc-depth: 4
theme: lumen
fontsize: large
code-fold: true
code-tools: true
code-summary: "Display code"
code-overflow: wrap
editor:
markdown:
wrap: 72
---
# **Section 1. GDELT Events Recorded in Poland: 2020 - 2023**
## **1.1 Breakdown of Events by Event Type**
We will start of with the very broad "Event Root Code" column. See Chapter 6 (pg 131) of CAMEO codebook for details.
Event Root Codes in focus:
- 09: Investigate
- 15: Exhibit Force Posture
- 17: Coerce
```{r, error = F, message = F, warning = F}
rm(list = ls())
#if (!require("pacman")) install.packages("pacman")
pacman::p_load(tidyverse, data.table, vtable,
lubridate, ggcharts, plyr,
gridExtra, RgoogleMaps, ggmap, mapproj)
## GDELT dataframe:
df <- fread("~/Desktop/soc_ace_2024/data/gdelt/gdelt_events_poland_cleaned.csv")
## Focus: Event Root Code:
df$EventRootCode <- as.character(df$EventRootCode)
df$EventRootCode <- str_pad(df$EventRootCode,
width=2,
side="left",
pad="0")
# table(df$EventRootCode)
df$Event_type <- ifelse(df$EventRootCode == "09", "Investigate",
ifelse(df$EventRootCode == "15", "Exhibit force posture",
ifelse(df$EventRootCode == "17", "Coerce", NA)))
df_backup <- df
table(df$Event_type)
fx01 <- function(data,
xv) {
ggplot(data,
aes(x = !!sym(xv))) +
geom_bar(fill = "black",
color = "black",
size = 1.5,
width = 0.75) +
labs(title = paste("Distribution of", xv),
x = xv,
y = "Count")+
# coord_flip()+
theme_bw()
}
fx02 <- function(data,
xv,
fctv) {
ggplot(data,
aes(x = !!sym(xv))) +
geom_bar(fill = "black",
color = "black",
size = 1.5,
width = 0.75) +
labs(title = paste("Distribution of", xv, "by year"),
x = xv,
y = "Count")+
facet_wrap(~year)+
# coord_flip()+
theme_bw()
}
fx01(df, "Event_type")
fx02(df, "Event_type", "year")
```
## **1.2 Maps of Events by Event Type**
The maps below display the count of event types in Poland.
**Interpretation:** <br>
Bigger circles around specific coordinates means higher count of events. <br>
(Larger circles = more events in that area).
## **1.3 Blank map (latitude/longitude only)**
```{r, error = F, message = F, warning = F}
# Register ggmap API for mapping:
#summary(df$ActionGeo_Lat)
#summary(df$ActionGeo_Long)
ggmap::register_stadiamaps(key = "ecb62ab3-c884-4be1-9e19-4a49f5f8bed0")
mapoutline <- get_map(location = c(left = 14.00, ## bottom left (lon)
bottom = 47.5, ## bottom left (lat)
right = 26.00, # bottom right (lon)
top = 56.00),
maptype = "outdoors",
source = "stadia",
color="bw")
print(ggmap(mapoutline))
```
## **1.4 All three event types**
```{r, error = F, message = F, warning = F}
df$Event_count <- 1
df01 <- ddply(df,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("All three event types in Poland, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.5 All three event types by year**
### 2020
```{r, error = F, message = F, warning = F}
df2020 <- df[df$year == "2020", ]
df2021 <- df[df$year == "2021", ]
df2022 <- df[df$year == "2022", ]
df2023 <- df[df$year == "2023", ]
## 2020:
df2020$Event_count <- 1
df202001 <- ddply(df2020,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map02 <- print(ggmap(mapoutline) +
geom_point(data = df202001,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("All three event types in Poland, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2021
```{r, error = F, message = F, warning = F}
## 2021:
df2021$Event_count <- 1
df202101 <- ddply(df2021,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map03 <- print(ggmap(mapoutline) +
geom_point(data = df202101,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("All three event types in Poland, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2022
```{r, error = F, message = F, warning = F}
## 2022:
df2022$Event_count <- 1
df202201 <- ddply(df2022,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map04 <- print(ggmap(mapoutline) +
geom_point(data = df202201,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("All three event types in Poland, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2023
```{r, error = F, message = F, warning = F}
## 2023:
df2023$Event_count <- 1
df202301 <- ddply(df2023,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map05 <- print(ggmap(mapoutline) +
geom_point(data = df202301,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("All three event types in Poland, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.6 Event type: Investigate**
```{r, error = F, message = F, warning = F}
df <- df_backup[df$Event_type == "Investigate", ]
df$Event_count <- 1
df01 <- ddply(df,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Investigate in Poland, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.7 Event type: Investigate by year**
### 2020
```{r, error = F, message = F, warning = F}
df2020 <- df[df$year == "2020", ]
df2021 <- df[df$year == "2021", ]
df2022 <- df[df$year == "2022", ]
df2023 <- df[df$year == "2023", ]
## 2020:
df2020$Event_count <- 1
df202001 <- ddply(df2020,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map02 <- print(ggmap(mapoutline) +
geom_point(data = df202001,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Investigate in Poland, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2021
```{r, error = F, message = F, warning = F}
## 2021:
df2021$Event_count <- 1
df202101 <- ddply(df2021,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map03 <- print(ggmap(mapoutline) +
geom_point(data = df202101,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Investigate in Poland, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2022
```{r, error = F, message = F, warning = F}
## 2022:
df2022$Event_count <- 1
df202201 <- ddply(df2022,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map04 <- print(ggmap(mapoutline) +
geom_point(data = df202201,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Investigate in Poland, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2023
```{r, error = F, message = F, warning = F}
## 2023:
df2023$Event_count <- 1
df202301 <- ddply(df2023,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map05 <- print(ggmap(mapoutline) +
geom_point(data = df202301,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Investigate in Poland, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.8 Event type: Coerce**
```{r, error = F, message = F, warning = F}
df <- df_backup[df_backup$Event_type == "Coerce", ]
df$Event_count <- 1
df01 <- ddply(df,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Coerce in Poland, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.9 Event type: Coerce by year**
### 2020
```{r, error = F, message = F, warning = F}
df2020 <- df[df$year == "2020", ]
df2021 <- df[df$year == "2021", ]
df2022 <- df[df$year == "2022", ]
df2023 <- df[df$year == "2023", ]
## 2020:
df2020$Event_count <- 1
df202001 <- ddply(df2020,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map02 <- print(ggmap(mapoutline) +
geom_point(data = df202001,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Coerce in Poland, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2021
```{r, error = F, message = F, warning = F}
## 2021:
df2021$Event_count <- 1
df202101 <- ddply(df2021,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map03 <- print(ggmap(mapoutline) +
geom_point(data = df202101,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Coerce in Poland, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2022
```{r, error = F, message = F, warning = F}
## 2022:
df2022$Event_count <- 1
df202201 <- ddply(df2022,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map04 <- print(ggmap(mapoutline) +
geom_point(data = df202201,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Coerce in Poland, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2023
```{r, error = F, message = F, warning = F}
## 2023:
df2023$Event_count <- 1
df202301 <- ddply(df2023,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map05 <- print(ggmap(mapoutline) +
geom_point(data = df202301,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Coerce in Poland, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.10 Event type: Exhibit force posture**
```{r, error = F, message = F, warning = F}
df <- df_backup[df_backup$Event_type == "Exhibit force posture", ]
df$Event_count <- 1
df01 <- ddply(df,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Exhibit force posture in Poland, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **1.11 Event type: Exhibit force posture by year**
### 2020
```{r, error = F, message = F, warning = F}
df2020 <- df[df$year == "2020", ]
df2021 <- df[df$year == "2021", ]
df2022 <- df[df$year == "2022", ]
df2023 <- df[df$year == "2023", ]
## 2020:
df2020$Event_count <- 1
df202001 <- ddply(df2020,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map02 <- print(ggmap(mapoutline) +
geom_point(data = df202001,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Exhibit force posture in Poland, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2021
```{r, error = F, message = F, warning = F}
## 2021:
df2021$Event_count <- 1
df202101 <- ddply(df2021,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map03 <- print(ggmap(mapoutline) +
geom_point(data = df202101,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Exhibit force posture in Poland, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2022
```{r, error = F, message = F, warning = F}
## 2022:
df2022$Event_count <- 1
df202201 <- ddply(df2022,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map04 <- print(ggmap(mapoutline) +
geom_point(data = df202201,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Exhibit force posture in Poland, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
### 2023
```{r, error = F, message = F, warning = F}
## 2023:
df2023$Event_count <- 1
df202301 <- ddply(df2023,
.(ActionGeo_Lat, ActionGeo_Long),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map05 <- print(ggmap(mapoutline) +
geom_point(data = df202301,
aes(x = ActionGeo_Long,
y = ActionGeo_Lat,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event type: Exhibit force posture in Poland, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
