classify_emotion: classifies the emotion (e.g. anger, disgust, fear, joy,...

In Jodavid/sentimentBR: Tools for Sentiment Analysis in English and Portuguese

classifies the emotion (e.g. anger, disgust, fear, joy, sadness, surprise) of a set of texts.

Description

classify_emotion Classifies the emotion (e.g. anger, disgust, fear, joy, sadness, surprise) of a set of texts using a naive Bayes classifier trained on Carlo Strapparava and Alessandro Valitutti's emotions lexicon.

Usage

classify_emotion(
  textColumns,
  algorithm = "bayes",
  prior = 1,
  verbose = FALSE,
  lang = "en",
  ...
)

Arguments

textColumns	A data.frame of text documents listed one per row.
algorithm	A string indicating whether to use the naive bayes algorithm or a simple voter algorithm.
prior	A numeric specifying the prior probability to use for the naive Bayes classifier.
verbose	A logical specifying whether to print detailed output regarding the classification process.
lang	Language, "en" for English and "pt" for Brazilian Portuguese.
...	Additional parameters to be passed into the create_matrix function.

Value

Returns an object of class data.frame with seven columns and one row for each document.

anger	The absolute log likelihood of the document expressing an angry sentiment.
disgust	The absolute log likelihood of the document expressing a disgusted sentiment.
fear	The absolute log likelihood of the document expressing a fearful sentiment.
joy	The absolute log likelihood of the document expressing a joyous sentiment.
sadness	The absolute log likelihood of the document expressing a sad sentiment.
surprise	The absolute log likelihood of the document expressing a surprised sentiment.
trust	The absolute log likelihood of the document expressing a trust sentiment.
negative	The absolute log likelihood of the document expressing a negative sentiment.
positive	The absolute log likelihood of the document expressing a positive sentiment.
anticipation	The absolute log likelihood of the document expressing a anticipation sentiment.
best_fit	The most likely sentiment category (e.g. anger, disgust, fear, joy, sadness, surprise) for the given text.

Author(s)

Timothy P. Jurka <[e-mail]> and Jodavid Ferreira <[e-mail]>

Examples

# DEFINE DOCUMENTS
documents <- c("I am very happy, excited, and optimistic.",
               "I am very scared, annoyed, and irritated.")

# CLASSIFY EMOTIONS
classify_emotion(documents,algorithm="bayes",verbose=TRUE, lang = "en")

# pt-BR
documentos <- c("Estou muito feliz, animado e otimista.",
               "Estou muito assustado e irritado.")

# CLASSIFY EMOTIONS
classify_emotion(documentos,algorithm="bayes",verbose=TRUE, lang = "pt")

Jodavid/sentimentBR documentation built on Oct. 9, 2022, 8:37 a.m.