add Q3 analysis code for weekly tweet count

DataAnalysis/Q3/q3_WeeklyTweetsCount.R

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+library(ggplot2)
+library(dplyr)
+
+# csv files
+foxnews <- read.csv("./UkraineConflictOnTwitter/SentimentAnalysis/data/q3/fox_news_Final_with_sentiment.csv")
+nytimes <- read.csv("./UkraineConflictOnTwitter/SentimentAnalysis/data/q3/new_york_times_Final_with_sentiment.csv")
+
+# remove replies (starting with '@')
+foxnews <- foxnews[!grepl('^@',foxnews$text),]
+nytimes <- nytimes[!grepl('^@',nytimes$text),]
+
+# modifying data
+
+# fox news
+# convert string to datetime
+foxnews$Date <- sub(" .*", "", foxnews$Date)
+foxnews$Date <- as.Date(foxnews$Date, format="%Y-%m-%d", tz="UTC")
+
+# create Week column
+foxnews <- foxnews %>% 
+  mutate(Week = cut.Date(foxnews$Date, breaks = "1 week", labels = FALSE)) %>% 
+  arrange(foxnews$Date)
+
+# calculate count by week
+foxnews_by_week <- foxnews %>%
+  group_by(Week) %>%
+  summarise(cnt = n()) %>%
+  arrange(Week)
+
+# ny times 
+
+# convert string to datetime
+nytimes$Date <- sub(" .*", "", nytimes$Date)
+nytimes$Date <- as.Date(nytimes$Date, format="%Y-%m-%d", tz="UTC")
+
+# create Week column
+nytimes <- nytimes %>% 
+  mutate(Week = cut.Date(nytimes$Date, breaks = "1 week", labels = FALSE)) %>% 
+  arrange(nytimes$Date)
+
+# calculate count by week
+nytimes_by_week <- nytimes %>%
+  group_by(Week) %>%
+  summarise(cnt = n()) %>%
+  arrange(Week)
+
+# line graph
+ggplot() +
+  theme_minimal() + 
+  theme(panel.background = element_blank()) +
+  ggtitle("Weekly Number of Tweets Containing Ukraine or Russia") +
+  labs(x='Week', y='Number of Tweets') +
+  theme(plot.title = element_text(hjust = 0.5, size=20, face='bold', margin = margin(t = 10, r = 0 , b = 10, l = 0))) +
+  theme(axis.title.x = element_text(face='bold', size=15, margin = margin(t = 10, b = 10, r = 0, l = 0))) +
+  theme(axis.title.y = element_text(face='bold', size=15, margin = margin(t = 0, b = 0, r = 10, l = 10))) +
+  theme(axis.text.x = element_text(size=13)) +
+  theme(axis.text.y = element_text(size=13)) +
+  theme(legend.title = element_text(face='bold', size=15)) +
+  theme(legend.text = element_text(size=15)) +
+  geom_line(aes(x = Week, y = cnt, color = "Fox News"), data = foxnews_by_week, size=1.5) + 
+  geom_line(aes(x = Week, y = cnt, color = "NY Times"), data = nytimes_by_week, size=1.5) +
+  scale_color_manual(name = "Y series", values = c("Fox News" = "#d9534f", "NY Times" = "#5cb85c")) + 
+  scale_x_continuous(breaks=c(1,4,11,16,23), labels=c("Dec 24th", "Jan 14th", "Feb 24th", "April 7th", "May 24th"))