Plot critics and audience ratings from Rotten Tomatoes

rotten_tomatoes_christmas_rankings.R

library(tidyverse)
library(rvest)
library(ggtext)
library(extrafont)

rt <- read_html("https://editorial.rottentomatoes.com/guide/best-christmas-movies/")

film_regex <- regex(
  "^([A-Za-z0-9.' ,-:&]* \\([0-9]{4,4}\\))\\n\\s+([0-9]{0,4})\\%\\n\\s+([0-9]{0,4})\\%"
)

# Wrangle data
rt_tbl <-
  rt %>%
  html_elements("h2") %>%
  html_text() %>%
  as_tibble() %>%
  mutate(value = trimws(value)) %>%
  mutate(
    film = str_extract(value, film_regex, group = 1),
    critics_review = str_extract(value, film_regex, group = 2),
    audience_review = str_extract(value, film_regex, group = 3)
  ) %>%
  drop_na() %>%
  select(-value)


# Make into format that makes it easier to plot
rt_tbl_long <-
  rt_tbl %>%
  mutate(critics_review = as.numeric(critics_review),
         audience_review = as.numeric(audience_review)) %>%
  mutate(film = fct_reorder(film, critics_review)) %>%  # Order by critics
  pivot_longer(cols = c(critics_review, audience_review),
               names_to = "review")


# Split out data
critics <- rt_tbl_long %>%
  filter(review == "critics_review")
audience <- rt_tbl_long %>%
  filter(review == "audience_review")


# Create plots
p <-
  rt_tbl_long %>%
  ggplot() +
  geom_segment(
    data = critics,
    aes(
      x = value,
      y = film,
      yend = audience$film,
      xend = audience$value
    ),
    color = "#aeb6bf",
    size = 1.5,
    #Note that I sized the segment to fit the points
    alpha = .5
  ) +
  geom_point(aes(x = value, y = film, color = review),
             size = 4,
             show.legend = TRUE) +
  ggtitle("Discrepancies between Tomatometer and Popcornmeter reviews on Rotten Tomatoes")
p


# Order data based on biggest difference
rt_tbl_long_diff <-
  rt_tbl %>%
  mutate(critics_review = as.numeric(critics_review),
         audience_review = as.numeric(audience_review)) %>%
  mutate(review_abs_diff = abs(critics_review - audience_review),
         review_raw_diff = critics_review - audience_review) %>%
  mutate(film = fct_reorder(film, review_abs_diff)) %>%  # Order by biggest diff
  pivot_longer(cols = c(critics_review, audience_review),
               names_to = "review")

# Split out data
critics_diff <- rt_tbl_long_diff %>%
  filter(review == "critics_review")
audience_diff <- rt_tbl_long_diff %>%
  filter(review == "audience_review")


# Create plots
p <-
  rt_tbl_long_diff %>%
  ggplot() +
  geom_segment(
    data = critics_diff,
    aes(
      x = value,
      y = film,
      yend = audience_diff$film,
      xend = audience_diff$value
    ),
    color = "#aeb6bf",
    size = 1.5,
    #Note that I sized the segment to fit the points
    alpha = .5
  ) +
  geom_point(aes(x = value, y = film, color = review),
             size = 4,
             show.legend = TRUE) +
  ggtitle("Discrepancies between Tomatometer and Popcornmeter reviews on Rotten Tomatoes",
          "Ordered by absolute value difference of critics review minus audience review")
p


# Order data based on biggest raw difference
rt_tbl_long_diff <-
  rt_tbl %>%
  mutate(critics_review = as.numeric(critics_review),
         audience_review = as.numeric(audience_review)) %>%
  mutate(review_abs_diff = abs(critics_review - audience_review),
         review_raw_diff = critics_review - audience_review) %>%
  mutate(film = fct_reorder(film, review_raw_diff)) %>%  # Order by biggest diff
  pivot_longer(cols = c(critics_review, audience_review),
               names_to = "review") %>%
  mutate(review = if_else(review == "critics_review", "Tomatometer", "Popcornmeter"))

# Split out data
critics_diff <- rt_tbl_long_diff %>%
  filter(review == "Tomatometer")
audience_diff <- rt_tbl_long_diff %>%
  filter(review == "Popcornmeter")


# Create plots
p <-
  rt_tbl_long_diff %>%
  ggplot() +
  geom_segment(
    data = critics_diff,
    aes(
      x = value,
      y = film,
      yend = audience_diff$film,
      xend = audience_diff$value
    ),
    color = "#aeb6bf",
    size = 1.5,
    #Note that I sized the segment to fit the points
    alpha = .5
  ) +
  geom_point(aes(x = value, y = film, color = review),
             size = 4,
             show.legend = TRUE) +
  scale_color_manual(values = c("#FFD600", "#F93001")) +
  ggtitle(
    "Discrepancies between Tomatometer and Popcornmeter reviews on Rotten Tomatoes",
    "Ordered by raw difference of critics review minus audience review"
  ) +
  labs(x = "Rating", y = "Film", color = "Review type") +
  scale_x_continuous(limits = c(0, 100),
                     label = scales::label_percent(scale = 1)) +
  theme_minimal() +
  theme(legend.position = "top", )
p +
  annotate(
    "rect",
    xmin = 10,
    xmax = 15,
    ymin = 0.5,
    ymax = 23.5,
    alpha = .2
  ) +
  annotate(
    "rect",
    xmin = 50,
    xmax = 55,
    ymin = 23.5,
    ymax = 42.5,
    alpha = .2
  ) +
  annotate(
    "rect",
    xmin = 10,
    xmax = 15,
    ymin = 42.5,
    ymax = 100.5,
    alpha = .2
  )