Sentiment analysis codebook for movie reviews

A qlm_codebook object defining instructions for sentiment analysis of movie reviews. Designed to work with data_corpus_LMRDsample but with an expanded polarity scale that includes a "mixed" category.

Usage

data_codebook_sentiment

Format

A qlm_codebook object containing:

name

Task name: "Movie Review Sentiment"

instructions

Coding instructions for analyzing movie review sentiment

schema

Response schema with two fields: polarity (Enum of "neg", "mixed", or "pos") and rating (Integer from 1 to 10)

role

Expert film critic persona

input_type

"text"

See also

qlm_codebook(), qlm_code(), qlm_compare(), data_corpus_LMRDsample

Examples

# View the codebook
data_codebook_sentiment
#> quallmer codebook: Sentiment analysis 
#>   Input type:   text
#>   Role:         You are a political communication analyst evaluating public ...
#>   Instructions: Analyze the sentiment of this text, on both a 1-10 scale and...
#>   Output schema:ellmer::TypeObject
#>   Levels:
#>     sentiment: nominal
#>     rating: ordinal

if (FALSE) { # \dontrun{
# Use with movie review corpus (requires API key)
coded <- qlm_code(data_corpus_LMRDsample[1:10],
                  data_codebook_sentiment,
                  model = "openai")

# Create multiple coded versions for comparison
coded1 <- qlm_code(data_corpus_LMRDsample[1:20],
                   data_codebook_sentiment,
                   model = "openai/gpt-4o-mini")
coded2 <- qlm_code(data_corpus_LMRDsample[1:20],
                   data_codebook_sentiment,
                   model = "openai/gpt-4o")

# Compare inter-rater reliability
comparison <- qlm_compare(coded1, coded2, by = "rating", level = "interval")
print(comparison)
} # }