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conversim (version 0.1.0)

sentiment_sim_dyads: Calculate sentiment similarity for multiple dyads

Description

This function calculates sentiment similarity over a sequence of conversation exchanges for multiple dyads.

Usage

sentiment_sim_dyads(conversations, window_size = 3)

Value

A list containing the sequence of similarities for each dyad and the overall average similarity

Arguments

conversations

A data frame with columns 'dyad_id', 'speaker', and 'processed_text'

window_size

An integer specifying the size of the sliding window

Examples

Run this code
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)

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