pushing other R files

DataAnalysis/Q3/NumberofWarRelated Tweets.R

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+library(ggplot2)
+library(dplyr)
+
+# csv file -- change the file path here
+#q1 <-  read.csv('/Volumes/GoogleDrive/My Drive/Spring 2022/Data Science Methodology/UkraineConflictOnTwitter/SentimentAnalysis/data/q1/all_tweets_emotions_with_sentiment.csv')
+#foxnews <- read.csv("/Volumes/GoogleDrive/My Drive/Spring 2022/Data Science Methodology/UkraineConflictOnTwitter/SentimentAnalysis/data/q3/fox_news_Final_with_sentiment.csv")
+#nytimes <- read.csv("/Volumes/GoogleDrive/My Drive/Spring 2022/Data Science Methodology/UkraineConflictOnTwitter/SentimentAnalysis/data/q3/new_york_times_Final_with_sentiment.csv")
+foxtitle <- read.csv("/Volumes/GoogleDrive/My Drive/Spring 2022/Data Science Methodology/UkraineConflictOnTwitter/SentimentAnalysis/data/q3/FoxNews_Sheikh_with_sentiment.csv")
+nytitle <- read.csv("/Volumes/GoogleDrive/My Drive/Spring 2022/Data Science Methodology/UkraineConflictOnTwitter/SentimentAnalysis/data/q3/NYT_Sheikh_with_sentiment.csv")
+
+nytitle$Source = "NYTimes"
+foxtitle$Source ="FoxNews"
+q1 <- rbind(nytitle, foxtitle)
+
+q1$text <- tolower(q1$text)
+#Only select the russia ukraine tweets
+tweets <- c('russia', "ukraine", 'invastion', 'invade', 'invades')
+q1 <- q1 %>% filter(grepl('russia|ukraine|invades|invasion', q1$text))
+
+
+## stacked bar plot ##
+
+# convert string to datetime
+q1$Date <- sub(" .*", "", q1$Date)
+q1$Date <- as.Date(q1$Date, format="%Y-%m-%d", tz="UTC")
+
+# create YearMonth column
+q1$YearMonth <- substr(q1$Date, 1,7)
+
+# create Week column
+q1 <- q1 %>% 
+  mutate(Week = cut.Date(q1$Date, breaks = "1 week", labels = FALSE)) %>% 
+  arrange(q1$Date)
+
+# calculate percentage of sentiment by week
+sentiment_by_week <- q1 %>%
+  group_by(Week, Source) %>%
+  summarise(cnt = n()) %>%
+  arrange(Week)
+
+# calculate percentage of sentiment by month
+
+
+# graph (by week)
+ggplot(sentiment_by_week, aes(y=cnt, x=Week, fill=Source, col=Source)) + 
+  geom_line(lwd=1.5) +
+  theme_minimal() + 
+  theme(panel.background = element_blank()) +
+  ggtitle("Weekly Number of Tweets Containing Ukraine or Russia") +
+  labs(x='Week', y='Frequency') +
+  theme(plot.title = element_text(hjust = 0.5, size=15, face='bold', margin = margin(t = 10, r = 0 , b = 10, l = 0))) +
+  theme(axis.title.x = element_text(face='bold', size=12, margin = margin(t = 10, b = 10, r = 0, l = 0))) +
+  theme(axis.title.y = element_text(face='bold', size=12, margin = margin(t = 0, b = 0, r = 10, l = 10))) +
+  theme(axis.text.x = element_text(angle=30, size=10)) +
+  theme(axis.text.y = element_text(size=10)) +
+  theme(legend.title = element_text(face='bold', size=10)) +
+  theme(legend.text = element_text(size=11)) +
+  scale_x_continuous(breaks=c(1,12,19,23), labels=c("Dec 1st", "Feb 24th", "April 12th", "April 30th"))
+#scale_color_manual('label', values=c('#d9534f', '#f0ad4e', '#5cb85c', '#5cb86c', '#5cb87c', '#5cb88c', '#5cb89c'))
+