vader_df {vader}

Get a dataframe of vader results for multiple text documents

Description

Use vader_df() to calculate the valence of multiple texts contained within a vector or column in a dataframe.

Usage

vader_df(text, incl_nt = T, neu_set = T, rm_qm = F)

Arguments

text

to be analyzed; for vader_df(), the text should be a single vector (e.g. 1 column)

incl_nt

defaults to T, indicates whether you wish to incl UNUSUAL n't contractions (e.g., yesn't) in negation analysis

neu_set

defaults to T, indicates whether you wish to count neutral words in calculations

rm_qm

defaults to T, indicates whether you wish to clean quotation marks from text (setting to F may result in errors)

Value

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".

N.B.

In the examples below, "yesn't" is an internet neologism meaning "no", "maybe yes, maybe no", "didn't", etc.

See Also

get_vader to get vader results for a single text document