This code has been lightly revised to make sure it works as of 2018-12-16.
This post will be a short demonstration of how the occurrence of emojis on Twitter can be analyzed using tidytools. We start loading the necessary packages.
library(tidyverse)
library(tidytext)
library(rtweet)I have decided that for this example that I would focus on tweets that include the hashtags #happy and #sad in the hope that both would include a similar number of emojis but hopefully of different groups. We will use the rtweet package which already conforms to the tidy principles. Notice the retryonratelimit = TRUE argument as the combined number of tweets (10000 + 10000 = 20000) is larger than the 15 min limit of 18000.
tweets_happy <- search_tweets("#happy", n = 10000, include_rts = FALSE)
tweets_sad <- search_tweets("#sad", n = 10000, include_rts = FALSE,
retryonratelimit = TRUE)we will safely save these tweets.
write_as_csv(tweets_happy, "tweets_happy.csv")
write_as_csv(tweets_sad, "tweets_sad.csv")Now we load this data.frame that contains information regarding the various emojis.
emoji <- readr::read_csv("https://raw.githubusercontent.com/EmilHvitfeldt/Emoji-table/master/emoji.csv")Next, we add the hash tag label as the emotion variable, next we tokenize all the tweets according to characters (this is done since a lot of the tweets didn’t use spaces emojis rendering them hard to detect.) and left join with the emoji data.frame such that we get the descriptions.
tweets_all <- bind_rows(
tweets_happy %>% mutate(emotion = "#happy"),
tweets_sad %>% mutate(emotion = "#sad")
)
emoji_all <- unnest_tokens(tweets_all, word, text,
token = "characters") %>%
select(word, emotion) %>%
left_join(emoji, by = c("word" = "utf")) %>%
filter(!is.na(shortname))Lastly, we create a simple faceted bar chart of the number of emojis used within each hashtag.
emoji_all %>%
count(word, emotion, shortname) %>%
group_by(emotion) %>%
arrange(desc(n)) %>%
top_n(10, n) %>%
ungroup() %>%
mutate(emoji = reorder(shortname, n)) %>%
ggplot(aes(emoji, n)) +
geom_col() +
facet_grid(emotion ~ ., scales = "free_y") +
coord_flip() +
theme_minimal() +
labs(title = "Emojis used in #happy and #sad tweets",
y = "Count", x = "")
Using the emoji data.frame allows us to gain quick insight with the descriptive short names.
session information
─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.1.0 (2021-05-18)
os macOS Big Sur 10.16
system x86_64, darwin17.0
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz America/Los_Angeles
date 2021-07-15
─ Packages ───────────────────────────────────────────────────────────────────
package * version date lib source
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[1] /Library/Frameworks/R.framework/Versions/4.1/Resources/library