GDELT Events: Moldova

Section 1. GDELT Events Recorded in Moldova: 2020 - 2023

1.01 Breakdown of events by keywords

Keywords: State actions

• ARREST
• CONFISCATION
• PERSECUTION
• SEIZE

Keywords: Non-state actions

• BLACK_MARKET
• CRIME_CARTELS
• DRUG_TRADE
• HUMAN_TRAFFICKING
• MIL_SELF_IDENTIFIED_ARMS_DEAL
• ORGANIZED_CRIME

Display code

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/gkg_v2/gkg_themes_moldova_cleaned.csv")

## Create different dataframes for each event types based on keywords:
df_arrest <- df[df$count_arrest >= 1, ]
df_confiscation <- df[df$count_confiscation >= 1, ]
df_persecution <- df[df$count_persecution >= 1, ]
df_seize <- df[df$count_seize >= 1, ]
df_black_market <- df[df$count_black_market >= 1, ]
df_crime_cartels <- df[df$count_crime_cartels >= 1, ]
df_drug_trade <- df[df$count_drug_trade >= 1, ]
df_human_trafficking <- df[df$count_human_trafficking >= 1, ]
df_arms_deal <- df[df$count_arms_deal >= 1, ]
df_organized_crime <- df[df$count_organized_crime >= 1, ]

df_backup <- df

df$arrest <- ifelse(df$count_arrest >=1, 1, 0)
df$confiscation <- ifelse(df$count_confiscation >=1, 1, 0)
df$persecution <- ifelse(df$count_persecution >=1, 1, 0)
df$seize <- ifelse(df$count_seize >=1, 1, 0)
df$black_market <- ifelse(df$count_black_market >=1, 1, 0)
df$crime_cartels <- ifelse(df$count_crime_cartels >=1, 1, 0)
df$drug_trade <- ifelse(df$count_drug_trade >=1, 1, 0)
df$human_trafficking <- ifelse(df$count_human_trafficking >=1, 1, 0)
df$arms_deal <- ifelse(df$count_arms_deal >=1, 1, 0)
df$organized_crime <- ifelse(df$count_organized_crime >=1, 1, 0)

## table(df$arrest)
## table(df$confiscation)
## table(df$persecution)
## table(df$seize)
## table(df$black_market)
## table(df$crime_cartels)
## table(df$drug_trade)
## table(df$human_trafficking)
## table(df$arms_deal)
## table(df$organized_crime)

## State Actions:
dfstate <- cbind.data.frame(df$arrest, df$confiscation, df$persecution, df$seize)
colnames(dfstate)[1:4] <- c("Arrest", "Confiscation", "Persecution", "Seize")
dfstate[] <- sapply(dfstate, as.numeric)
dfstate[is.na(dfstate)] <- 0

tab01 <- data.frame(values=colSums(dfstate, 
                                 na.rm=TRUE), 
                  names = names(dfstate))

p01 <- ggplot(data=tab01, 
       aes(x=names, 
           y=values)) +
  geom_bar(stat="identity", 
           fill = "black", 
             color = "black", 
             size = 1.5,
             width = 0.75)+
  ylim(0, 80)+
    labs(title = paste("Moldova: state actions"),
         x = "",
         y = "Count")+
  theme_bw()

p01 <- p01+ theme(axis.text.x = element_text(angle = 45, hjust = 1))


#p01 

## Non-nonstate Actions:
dfnonstate <- cbind.data.frame(df$black_market, df$crime_cartels, df$drug_trade, 
                               df$human_trafficking, df$arms_deal, df$organized_crime)

colnames(dfnonstate)[1:6] <- c("Black_market", "Cartels", "Drug_trade",
                               "Human_trafficking", "Arms_deal", "Organized_crime")

dfnonstate[] <- sapply(dfnonstate, as.numeric)
dfnonstate[is.na(dfnonstate)] <- 0

tab02 <- data.frame(values=colSums(dfnonstate, 
                                 na.rm=TRUE), 
                  names = names(dfnonstate))

p02 <- ggplot(data=tab02, 
       aes(x=names, 
           y=values)) +
  geom_bar(stat="identity", 
           fill = "black", 
             color = "black", 
             size = 1.5,
             width = 0.75)+
  ylim(0, 80)+
    labs(title = paste("Moldova: non-state actions"),
         x = "",
         y = "Count")+
  theme_bw()

p02 <- p02+ theme(axis.text.x = element_text(angle = 45, hjust = 1))

p01 | p02

1.02 Maps of events by keyword

The maps below display the count of event types by keyword in Moldova.

Interpretation:
Bigger circles around specific coordinates means higher count of events.
(Larger circles = more events in that area).

Blank map:

Display code

# 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 = 26.00, ## bottom left (lon)
                                   bottom = 45.00, ## bottom left (lat)
                                   right = 32.00, # bottom right (lon)
                                   top = 49.00), 
                      maptype = "outdoors", 
                      source = "stadia",
                      color="bw")

print(ggmap(mapoutline))

1.03 Event type: all keywords

2020 - 2023

Display code

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: all keywords in Moldova, 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())

2020

Display code

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: all keywords in Moldova, 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

Display code

## 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: all keywords in Moldova, 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

Display code

## 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: all keywords in Moldova, 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

Display code

## 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: all keywords in Moldova, 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())

1.04 Event type: state actions

2020 - 2023

Display code

df$state <- ifelse(df$arrest == 1, 1,
            ifelse(df$confiscation == 1, 1,
            ifelse(df$persecution == 1, 1,
            ifelse(df$seize == 1, 1, 0))))

dfstate <- df[(df$state == 1), ]

dfstate$Event_count <- 1

df01 <- ddply(dfstate, 
            .(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: state actions in Moldova, 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())

2020

Display code

df2020 <- dfstate[dfstate$year == "2020", ]
df2021 <- dfstate[dfstate$year == "2021", ]
df2022 <- dfstate[dfstate$year == "2022", ]
df2023 <- dfstate[dfstate$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: state actions in Moldova, 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

Display code

## 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: state actions in Moldova, 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

Display code

## 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: state actions in Moldova, 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

Display code

## 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: state actions in Moldova, 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())

1.05 Event type: non-state actions

2020 - 2023

Display code

df$nonstate <- ifelse(df$black_market == 1, 1,
               ifelse(df$crime_cartels == 1, 1,
               ifelse(df$drug_trade == 1, 1,
               ifelse(df$human_trafficking == 1, 1,
               ifelse(df$arms_deal == 1, 1,
               ifelse(df$organized_crime == 1, 1, 0))))))

dfnonstate <- df[(df$nonstate == 1), ]

dfnonstate$Event_count <- 1

df01 <- ddply(dfnonstate, 
            .(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: non-state actions in Moldova, 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())

2020

Display code

df2020 <- dfnonstate[dfnonstate$year == "2020", ]
df2021 <- dfnonstate[dfnonstate$year == "2021", ]
df2022 <- dfnonstate[dfnonstate$year == "2022", ]
df2023 <- dfnonstate[dfnonstate$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: non-state actions in Moldova, 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

Display code

## 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: non-state actions in Moldova, 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

Display code

## 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: non-state actions in Moldova, 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

Display code

## 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: non-state actions in Moldova, 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())

1.06 Event type: Arrest

2020 - 2023

Display code

dfarrest <- df[(df$arrest == 1), ]

dfarrest$Event_count <- 1

df01 <- ddply(dfarrest, 
            .(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: arrest in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfarrest[dfarrest$year == "2020", ]
df2021 <- dfarrest[dfarrest$year == "2021", ]
df2022 <- dfarrest[dfarrest$year == "2022", ]
df2023 <- dfarrest[dfarrest$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: arrest in Moldova, 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

Display code

## 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: arrest in Moldova, 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

Display code

## 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: arrest in Moldova, 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

Display code

## 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: arrest in Moldova, 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())

1.07 Event type: Confiscation

2020 - 2023

Display code

dfconfiscation <- df[(df$confiscation == 1), ]

dfconfiscation$Event_count <- 1

df01 <- ddply(dfconfiscation, 
            .(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: confiscation in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfconfiscation[dfconfiscation$year == "2020", ]
df2021 <- dfconfiscation[dfconfiscation$year == "2021", ]
df2022 <- dfconfiscation[dfconfiscation$year == "2022", ]
df2023 <- dfconfiscation[dfconfiscation$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: confiscation in Moldova, 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

Display code

## 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: confiscation in Moldova, 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

Display code

## 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: confiscation in Moldova, 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

Display code

## 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: confiscation in Moldova, 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())

1.08 Event type: Persecution

2020 - 2023

Display code

dfpersecution <- df[(df$persecution == 1), ]

dfpersecution$Event_count <- 1

df01 <- ddply(dfpersecution, 
            .(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: persecution in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfpersecution[dfpersecution$year == "2020", ]
df2021 <- dfpersecution[dfpersecution$year == "2021", ]
df2022 <- dfpersecution[dfpersecution$year == "2022", ]
df2023 <- dfpersecution[dfpersecution$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: persecution in Moldova, 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

Display code

## 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: persecution in Moldova, 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

Display code

## 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: persecution in Moldova, 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

Display code

## 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: persecution in Moldova, 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())

1.09 Event type: Seize

2020 - 2023

Display code

dfseize <- df[(df$seize == 1), ]

dfseize$Event_count <- 1

df01 <- ddply(dfseize, 
            .(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: seize in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfseize[dfseize$year == "2020", ]
df2021 <- dfseize[dfseize$year == "2021", ]
df2022 <- dfseize[dfseize$year == "2022", ]
df2023 <- dfseize[dfseize$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: seize in Moldova, 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

Display code

## 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: seize in Moldova, 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

Display code

## 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: seize in Moldova, 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

Display code

## 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: seize in Moldova, 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: Black market

2020 - 2023

Display code

dfblack_market <- df[(df$black_market == 1), ]

dfblack_market$Event_count <- 1

df01 <- ddply(dfblack_market, 
            .(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: black_market in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfblack_market[dfblack_market$year == "2020", ]
df2021 <- dfblack_market[dfblack_market$year == "2021", ]
df2022 <- dfblack_market[dfblack_market$year == "2022", ]
df2023 <- dfblack_market[dfblack_market$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: black_market in Moldova, 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

Display code

## 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: black_market in Moldova, 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

Display code

## 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: black_market in Moldova, 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

Display code

## 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: black_market in Moldova, 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: Cartels

2020 - 2023

Display code

dfcrime_cartels <- df[(df$crime_cartels == 1), ]

dfcrime_cartels$Event_count <- 1

df01 <- ddply(dfcrime_cartels, 
            .(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: crime_cartels in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfcrime_cartels[dfcrime_cartels$year == "2020", ]
df2021 <- dfcrime_cartels[dfcrime_cartels$year == "2021", ]
df2022 <- dfcrime_cartels[dfcrime_cartels$year == "2022", ]
df2023 <- dfcrime_cartels[dfcrime_cartels$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: crime_cartels in Moldova, 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

Display code

## 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: crime_cartels in Moldova, 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

Display code

## 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: crime_cartels in Moldova, 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

Display code

## 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: crime_cartels in Moldova, 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())

1.12 Event type: Drug trade

2020 - 2023

Display code

dfdrug_trade <- df[(df$drug_trade == 1), ]

dfdrug_trade$Event_count <- 1

df01 <- ddply(dfdrug_trade, 
            .(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: drug_trade in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfdrug_trade[dfdrug_trade$year == "2020", ]
df2021 <- dfdrug_trade[dfdrug_trade$year == "2021", ]
df2022 <- dfdrug_trade[dfdrug_trade$year == "2022", ]
df2023 <- dfdrug_trade[dfdrug_trade$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: drug_trade in Moldova, 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

Display code

## 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: drug_trade in Moldova, 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

Display code

## 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: drug_trade in Moldova, 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

Display code

## 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: drug_trade in Moldova, 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())

1.13 Event type: Human trafficking

2020 - 2023

Display code

dfhuman_trafficking <- df[(df$human_trafficking == 1), ]

dfhuman_trafficking$Event_count <- 1

df01 <- ddply(dfhuman_trafficking, 
            .(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: human_trafficking in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfhuman_trafficking[dfhuman_trafficking$year == "2020", ]
df2021 <- dfhuman_trafficking[dfhuman_trafficking$year == "2021", ]
df2022 <- dfhuman_trafficking[dfhuman_trafficking$year == "2022", ]
df2023 <- dfhuman_trafficking[dfhuman_trafficking$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: human_trafficking in Moldova, 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

Display code

## 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: human_trafficking in Moldova, 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

Display code

## 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: human_trafficking in Moldova, 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

Display code

## 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: human_trafficking in Moldova, 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())

1.14 Event type: Arms deal

2020 - 2023

Display code

dfarms_deal <- df[(df$arms_deal == 1), ]

dfarms_deal$Event_count <- 1

df01 <- ddply(dfarms_deal, 
            .(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: arms_deal in Moldova, 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())

2020

Display code

### 2020

df2020 <- dfarms_deal[dfarms_deal$year == "2020", ]
df2021 <- dfarms_deal[dfarms_deal$year == "2021", ]
df2022 <- dfarms_deal[dfarms_deal$year == "2022", ]
df2023 <- dfarms_deal[dfarms_deal$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: arms_deal in Moldova, 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

Display code

## 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: arms_deal in Moldova, 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

Display code

## 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: arms_deal in Moldova, 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

Display code

## 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: arms_deal in Moldova, 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())

1.15 Event type: Organized crime

2020 - 2023

Display code

dforganized_crime <- df[(df$organized_crime == 1), ]

dforganized_crime$Event_count <- 1

df01 <- ddply(dforganized_crime, 
            .(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: organized_crime in Moldova, 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())

2020

Display code

### 2020

df2020 <- dforganized_crime[dforganized_crime$year == "2020", ]
df2021 <- dforganized_crime[dforganized_crime$year == "2021", ]
df2022 <- dforganized_crime[dforganized_crime$year == "2022", ]
df2023 <- dforganized_crime[dforganized_crime$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: organized_crime in Moldova, 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

Display code

## 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: organized_crime in Moldova, 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

Display code

## 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: organized_crime in Moldova, 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

Display code

## 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: organized_crime in Moldova, 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())