Adds new column(s) to dataframe returned by rtweet get_timeline() function with default parameters based on user specified input

Returns a new dataframe containing additional columns that were not in the original Generatable columns include... text_only: strips emojis, hashtags, and hyperlinks from the text column word_count: counts the number of words contained in the text_only column emojis: contains the extracted emojis from text proportion_of_avg_retweets: a proportion value of how many retweets a tweet received compared to the account average proportion_of_avg_favorites: a proportion value of how many favorites a tweet received compared to the account average

clean_df(
  raw_tweets_df,
  text_only = TRUE,
  word_count = TRUE,
  emojis = TRUE,
  proportion_of_avg_retweets = TRUE,
  proportion_of_avg_favorites = TRUE
)

Arguments

raw_tweets_df	dataframe
text_only	bool
word_count	bool
emojis	bool
proportion_of_avg_retweets	bool
proportion_of_avg_favorites	bool

Value

dataframe

Examples

text <- c("example tweet text 1 @user2 @user",
"#example #tweet 2 ",
"example tweet 3 https://t.co/G4ziCaPond",
"example tweet 4")
retweet_count <- c(43, 12, 24, 29)
favorite_count <- c(85, 41, 65, 54)
raw_df <- data.frame(text, retweet_count, favorite_count)
clean_df(raw_df)
#>                                      text retweet_count favorite_count
#> 1       example tweet text 1 @user2 @user            43             85
#> 2                      #example #tweet 2             12             41
#> 3 example tweet 3 https://t.co/G4ziCaPond            24             65
#> 4                         example tweet 4            29             54
#>              text_only word_count emojis prptn_rts_vs_avg
#> 1 example tweet text 1          4               1.5925926
#> 2                    2          1               0.4444444
#> 3      example tweet 3          3               0.8888889
#> 4      example tweet 4          3               1.0740741
#>   prptn_favorites_vs_avg
#> 1              1.3877551
#> 2              0.6693878
#> 3              1.0612245
#> 4              0.8816327
clean_df(raw_df, emojis = FALSE)
#>                                      text retweet_count favorite_count
#> 1       example tweet text 1 @user2 @user            43             85
#> 2                      #example #tweet 2             12             41
#> 3 example tweet 3 https://t.co/G4ziCaPond            24             65
#> 4                         example tweet 4            29             54
#>              text_only word_count prptn_rts_vs_avg prptn_favorites_vs_avg
#> 1 example tweet text 1          4        1.5925926              1.3877551
#> 2                    2          1        0.4444444              0.6693878
#> 3      example tweet 3          3        0.8888889              1.0612245
#> 4      example tweet 4          3        1.0740741              0.8816327