sentiment_sim_dyads {conversim} | R Documentation |
This function calculates sentiment similarity over a sequence of conversation exchanges for multiple dyads.
sentiment_sim_dyads(conversations, window_size = 3)
conversations |
A data frame with columns 'dyad_id', 'speaker', and 'processed_text' |
window_size |
An integer specifying the size of the sliding window |
A list containing the sequence of similarities for each dyad and the overall average similarity
library(lme4)
convs <- data.frame(
dyad_id = c(1, 1, 1, 1, 2, 2, 2, 2),
speaker = c("A", "B", "A", "B", "C", "D", "C", "D"),
processed_text = c("i love pizza", "me too favorite food",
"whats your favorite topping", "enjoy pepperoni mushrooms",
"i prefer pasta", "pasta delicious like spaghetti carbonara",
"ever tried making home", "yes quite easy make")
)
sentiment_sim_dyads(convs, window_size = 2)