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library("RCurl")
library("jsonlite")
library("ggplot2")
library("RColorBrewer")
library("scales")
library("gridExtra")
api.key <- "yourAPIkey"
rt <- getURI(paste0("http://api.rottentomatoes.com/api/public/v1.0/lists/dvds/top_rentals.json?apikey=", api.key, "&limit=50"))
rt <- fromJSON(rt)
title <- rt$movies$title
critics <- rt$movies$ratings$critics_score
audience <- rt$movies$ratings$audience_score
df <- data.frame(title=title, critic.score=critics,
audience.score=audience)
# Top 50 rentals, max returnable
ggplot(df, aes(x=critic.score, y=audience.score)) +
geom_text(aes(label=title, col=1/(critic.score - audience.score)))
# how can we get more? similar chaining
# STILL at most 5 per film (sigh)
getRatings <- function(id){
sim.1 <- getURI(paste0("http://api.rottentomatoes.com/api/public/v1.0/movies/",
id, "/similar.json?apikey=",
api.key, "&limit=5"))
sim <- fromJSON(sim.1)
#cat(sim$movies$title)
d <- data.frame(id = sim$movies$id,
title = sim$movies$title,
crit = sim$movies$ratings$critics_score,
aud = sim$movies$ratings$audience_score)
return(d)
}
rt.results <- function(idlist){
r <- sapply(unique(as.character(idlist)), getRatings, simplify=F)
r <- do.call(rbind, r)
return(r)
}
# Maybe this could be done via a cool recursion using Recall
r1 <- rt.results(rt$movies$id)
r2 <- rt.results(r1$id)
r3 <- rt.results(r2$id)
r4 <- rt.results(r3$id)
r5 <- rt.results(r4$id)
r6 <- rt.results(r5$id)
r7 <- rt.results(r6$id)
f <- function(x)
(5**x)-1
# Fig. 1: Number of films gathered via recursive descent
# of 'similar films' lists.
dev.off()
options(scipen=99)
pdf(4, 4, file="rottenTomatoHits.pdf")
par(cex.axis=.7, pch=20, mar=c(4,3,1,1), mgp=c(1.5,.3,0), tck=-.02)
plot(1:7, f(1:7), type="b", xlab="Recursions", ylab="Number of hits",
log="y", col=muted("blue"), lwd=2, ylim=c(4, 1e5))
lines(1:7, c(nrow(r1), nrow(r2), nrow(r3), nrow(r4), nrow(r5),
nrow(r6), nrow(r7)), type="b", col=muted("red"), lwd=2)
legend("bottomright", col=c(muted("blue"), muted("red")), pch=20, lwd=2,
legend=c(expression(Max~(5^x)), "Realised"), bty="n", lty="47")
dev.off()
r <- rbind(r1, r2, r3, r4, r5, r6, r7)
# 1279 unique films
ru <- r[!duplicated(as.character(r$id)),]
# Films with insufficient critics reviews get -1 score
ru[which(ru$crit == -1),]
ru <- ru[ru$crit != -1,]
ru$diff <- ru$crit - ru$aud
pcc <- cor(ru$crit, ru$aud)
# Overview figure: Show all critics vs. audience scores
# and highlight the titles of outliers
svg(7, 6, file="overview.svg")
ggplot(ru, aes(x=crit, y=aud, col=diff)) +
geom_point() +
coord_cartesian(xlim=c(-10,110), ylim=c(-10,110)) +
scale_color_gradientn(colours=brewer.pal(11, "RdYlBu"),
breaks=seq(-60,40, length.out=11),
labels=c("Underrated", rep("", 4),
"Agree", rep("", 4),
"Overrated")) +
geom_text(aes(label=ifelse(diff < quantile(diff, .005) |
diff > quantile(diff, .995), as.character(title), ""),
size=abs(diff)),
hjust=0, vjust=0, angle=45) +
scale_size_continuous(range=c(2,4), guide="none") +
labs(list(x="Critic's score", y="Audience score",
col="")) +
annotate("text", 3, 3,
label=paste0("rho ==", format(pcc, digits=2)),
parse=T)
dev.off()
tab <- ru
colnames(tab) <- c("id", "Title", "Critics", "Audience", "Difference")
# Most underrated films:
grid.newpage()
grid.draw(tableGrob(tab[order(tab$Difference),][1:15,-1], show.rownames=F))
# Most overrated:
grid.newpage()
grid.draw(tableGrob(tab[order(tab$Difference, decreasing=T),][1:15,-1], show.rownames=F))
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