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library(ggplot2)
positions = c("Travel and Holidays", "Finances", "Learning and Career", "Mental Wellbeing",
"Relationships", "Physical Health")
# What are the most popular resolutions?
p1 <- ggplot(twitter_df[twitter_df$Resolution.type != "",], aes(x = Resolution.type, fill = Resolution.type)) +
geom_bar() +
coord_flip() +
ggtitle("Number of tweets by resolution type") +
scale_x_discrete(limits = positions, name = "") +
scale_y_continuous(name = "Number of tweets") +
scale_fill_brewer(palette = "Paired") +
theme_bw() +
theme(plot.title = element_text(size = 12, family = "Tahoma", face = "bold"),
text = element_text(size = 10, family = "Tahoma")) +
labs(fill = "Resolution") +
geom_text(stat = "count", aes(label = ..count..),
family = "Tahoma", size = 3, hjust = 1)
p1
# How do people feel about their resolutions?
p2 <- ggplot(data = twitter[twitter$Resolution.type != "" & twitter$Compound != 0,],
aes(x = Compound, colour = Resolution.type)) +
geom_density(position="identity", fill = NA, size = 0.8) +
ggtitle("Density plots of overall sentiment by resolution type") +
scale_x_continuous(name = "Compound sentiment score") +
scale_y_continuous(name = "Density") +
scale_colour_brewer(palette = "Paired") +
theme_bw() +
theme(plot.title = element_text(size = 12, family = "Tahoma", face = "bold"),
text = element_text(size = 10, family = "Tahoma"),
legend.position="none") +
facet_wrap( ~ Resolution.type, ncol=2)
p2
# Get median compound resolutions
library(knitr)
kable(aggregate(Compound ~ Resolution.type,
data = twitter[twitter$Compound != 0 & twitter$Resolution.type != "",],
FUN = median), digits = 3, col.names = c("Resolution", "Sentiment Score"))
# How do people’s friends feel about their resolutions?
library(plyr)
agg_twitter <- ddply(twitter[twitter$Resolution.type != "" & twitter$Compound != 0,],
"Resolution.type", summarise,
mdn.compound = median(Compound),
num.resolutions = length(Resolution.type),
prop.favourite = sum(Five.or.more.favourites) / length(Resolution.type))
p3 <- ggplot(data = agg_twitter, aes(x = mdn.compound, y = prop.favourite,
size = num.resolutions,
colour = Resolution.type)) +
geom_point() +
scale_size_area(max_size = 25) +
ggtitle("Weighted scatterplot of tweet sentiment against number of favourites") +
scale_x_continuous(limits = c(0.1, 0.6), name = "Compound sentiment score (median)") +
scale_y_continuous(limits = c(0.14, 0.23), name = "Received five or more favourites (%)") +
scale_colour_brewer(palette = "Paired") +
labs(colour = "Resolution", size = "Number of tweets") +
theme_bw() +
theme(plot.title = element_text(size = 12, family = "Tahoma", face = "bold"),
text = element_text(size = 10, family = "Tahoma"))
p3
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