In jvfe/twitterExplorer: Explores Twitter data using R

devtools::load_all()
library(flexdashboard)
library(rtweet)
library(vroom)
library(dplyr)

rstats_tweets <- readData("data/tweets.csv.gz")

timeline <- make_by_day_metrics(rstats_tweets)

n_tweets <- get_unique_value(rstats_tweets, text)

n_retweets <- rstats_tweets %>%
  pull(retweet_count) %>%
  sum()

n_users <- get_unique_value(rstats_tweets, user_id)

n_likes <- rstats_tweets %>%
  pull(favorite_count) %>%
  sum()

tweets_today <- rstats_tweets %>%
  filter(lubridate::date(created_at) == lubridate::today())

Row

#rstats Tweets

valueBox(n_tweets, icon = "fa-comments")

#rstats Retweets

valueBox(n_retweets, icon = "fa-retweet")

Users

valueBox(n_users, icon = "fa-user")

Likes

valueBox(n_likes, icon = "fa-heart")

Row {.tabset .tabset-fade}

Tweet volume

plot_tweet_volume(timeline)

Tweets by Hour of Day

plot_tweet_by_hour(rstats_tweets)

Row

💗 Most Liked Tweet Today {.tweet-box}

most_liked_url <- tweets_today %>%
  slice_max(favorite_count, with_ties = FALSE)

get_tweet_embed(most_liked_url$screen_name, most_liked_url$status_id)

✨ Most Retweeted Tweet Today {.tweet-box}

most_retweeted <- tweets_today %>%
  slice_max(retweet_count, with_ties = FALSE)

get_tweet_embed(most_retweeted$screen_name, most_retweeted$status_id)

🎉 Most Recent {.tweet-box}

most_recent <- tweets_today %>%
  slice_max(created_at, with_ties = FALSE)

get_tweet_embed(most_recent$screen_name, most_recent$status_id)

jvfe/twitterExplorer documentation built on Dec. 21, 2021, 4:22 a.m.