predictGWP: Predict function for new data.

In keblu/GWP: Generalized Word Power Approach

Description

Ouput sentiment value given a fitted model and frequency table.

Usage

predictGWP(frequencies, model)

Arguments

frequencies	frequencies data.table generated using the function computeFrequencies.
model	Score model generated with fitGWP.

Value

A data.table with the following element:

• regID: regression ID.

• SentimentScores: predicted sentiment scores.

Examples

# Load example data
data("corpus",  package = "GWP")
data("vix",  package = "GWP")
# Setup the lexicons
sentimentWord <- sentometrics::list_lexicons$LM_en$x
shifterWord <- sentometrics::list_valence_shifters$en[, c("x", "y")]

# Generate the frequency data
frequencies <- computeFrequencies(corpus[1:991, ], sentimentWord, shifterWord, clusterSize = 5)

# Calibrate the lexicon
res <- fitGWP(frequencies = frequencies, responseData = vix)

newFrequencies <- computeFrequencies(corpus[-1:-991, ], sentimentWord, shifterWord, clusterSize = 5)
pred <- predictGWP(newFrequencies, res)

keblu/GWP documentation built on June 15, 2020, 11:43 p.m.