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Christianity Today Goes Viral
library(rtweet)
library(socsci)
## Scraping and Joining ####
rt <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt1 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt2 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt3 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt4 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt5 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt6 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
rt7 <- search_tweets(
"https://www.christianitytoday.com/ct/2019/december-web-only/trump-should-be-removed-from-office.html", n = 18000, include_rts = TRUE
)
all <- bind_rows(rt, rt1, rt2, rt3, rt4, rt5, rt6)
all <- all %>% distinct(status_id, .keep_all = TRUE)
## Tweet Volume ####
all$date <- date(all$created_at)
all$date2 <- round_date(all$created_at, "1 mins")
graph <- all %>%
group_by(date2) %>%
count()
graph %>%
ggplot(., aes(date2, y = n, fill = n)) +
scale_fill_gradient(low = "#AAB0B1", high = "#E11A23") +
geom_col() +
theme_gg("Abel") +
labs(x = "Greenwich Mean Time", y = "Tweets per Minute", title = "Volume of Tweets about the CT Editorial", caption = "@ryanburge\nData: Twitter REST API") +
ggsave("E://vel_ct.png", type = "cairo-png")
## Sentiment Analysis ####
reg_words <- "([^A-Za-z_\\d#@']|'(?![A-Za-z_\\d#@]))"
tidy_tweets <- all %>%
filter(!str_detect(text, "^RT")) %>%
mutate(text = str_replace_all(text, "https://t.co/[A-Za-z\\d]+|http://[A-Za-z\\d]+|&amp;|&lt;|&gt;|RT|https", "")) %>%
unnest_tokens(word, text) %>%
filter(!word %in% stop_words$word,
str_detect(word, "[a-z]"))
afinn <- get_sentiments("afinn")
tidy_tweets <- tidy_tweets %>%
inner_join(afinn)
fin1 <- tidy_tweets %>%
filter(value > 0) %>%
group_by(date2) %>%
summarise(sum = sum(value)) %>%
mutate(type = "Positive")
fin2 <- tidy_tweets %>%
filter(value < 0) %>%
group_by(date2) %>%
summarise(sum = sum(value)) %>%
mutate(type = "Negative")
fin3 <- tidy_tweets %>%
group_by(date2) %>%
summarise(sum = sum(value)) %>%
mutate(type = "Overall")
fin <- bind_rows(fin1, fin2, fin3)
fin %>%
ggplot(., aes(x = date2, y = sum, color = type, group = type)) +
geom_point(size=3, color="white") +
geom_point(size=2, shape=1) +
geom_point(size=1, shape=19) +
scale_color_manual(values = c("#D51B1E", "#AAB0B1", "navyblue")) +
geom_smooth(se = FALSE, linetype = "twodash") +
theme_gg("Abel") +
theme(legend.position = "bottom") +
labs(x = "Greenwich Mean Time", y = "Overall Sentiment", title = "The Sentiment of Tweets About the CT Editorial", caption = "@ryanburge\nData: Twitter REST API") +
ggsave("E://sentiment_CT.png", type = "cairo-png")
graph <- tidy_tweets %>%
filter(value < 0) %>%
ct(word) %>%
arrange(-n) %>%
top_n(25)
graph %>%
filter(word != "shit") %>%
ggplot(., aes(x = reorder(word, n), y = n, fill = n)) +
geom_col(color = "black") +
coord_flip() +
theme_gg("Abel") +
scale_fill_gradient(low = "#AAB0B1", high = "#D51B1E") +
labs(x = "", y = "", title = "Most Used Negative Words", caption = "@ryanburge\nData: Twitter REST API") +
ggsave("E://neg_words.png", type = "cairo-png")
graph <- tidy_tweets %>%
filter(value > 0) %>%
ct(word) %>%
arrange(-n) %>%
top_n(25)
graph %>%
filter(word != "shit") %>%
ggplot(., aes(x = reorder(word, n), y = n, fill = n)) +
geom_col(color = "black") +
coord_flip() +
theme_gg("Abel") +
scale_fill_gradient(low = "#AAB0B1", high = "navyblue") +
labs(x = "", y = "", title = "Most Used Positive Words", caption = "@ryanburge\nData: Twitter REST API") +
ggsave("E://pos_words.png", type = "cairo-png")
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