Use vader_df() to calculate the valence of multiple texts contained within a vector or column in a dataframe.
vader_df(text, incl_nt = T, neu_set = T, rm_qm = F)to be analyzed; for vader_df(), the text should be a single vector (e.g. 1 column)
defaults to T, indicates whether you wish to incl UNUSUAL n't contractions (e.g., yesn't) in negation analysis
defaults to T, indicates whether you wish to count neutral words in calculations
defaults to T, indicates whether you wish to clean quotation marks from text (setting to F may result in errors)
A dataframe containing the valence score for each word; an overall, compound valence score for the text; the weighted percentage of positive, negative, and neutral words in the text; and the frequency of the word "but".
In the examples below, "yesn't" is an internet neologism meaning "no", "maybe yes, maybe no", "didn't", etc.
get_vader to get vader results for a single text document