sentimentr

sentimentr

Sentence-level sentiment with valence shifters.

Basic Usage

library(sentimentr)

# Sentiment of text
text <- "I really love this product. It's not bad at all."
sentiment(text)

# Returns data frame with:
# element_id, sentence_id, word_count, sentiment

Sentiment Scores

# Single text
result <- sentiment(text)

# Multiple texts
texts <- c("I love this!", "This is terrible.", "Not bad.")
result <- sentiment(texts)

# By sentence
result <- sentiment_by(texts)

Valence Shifters

# sentimentr handles:
# - Negators: "not good" -> negative
# - Amplifiers: "very good" -> more positive
# - De-amplifiers: "barely good" -> less positive
# - Adversative conjunctions: "good but expensive"

text <- "I don't like this. It's not very good."
sentiment(text)  # Correctly handles negation

Sentiment by Group

# Group by variable
df <- data.frame(
  text = c("Great product!", "Terrible service.", "Love it!"),
  group = c("A", "B", "A")
)

sentiment_by(df$text, df$group)

Emotion Detection

# Get emotions
emotion(text)

# Specific emotions
emotion_by(text)

# Returns: anger, anticipation, disgust, fear, joy,
#          sadness, surprise, trust

Profanity Detection

# Check for profanity
profanity(text)

# By group
profanity_by(texts, grouping_var)

Highlighting

# Highlight sentiment in text
result <- sentiment(text)
highlight(result)

# Returns HTML with color-coded sentiment

Custom Lexicon

# Create custom polarity table
my_lexicon <- lexicon::hash_sentiment_jockers_rinker

# Add custom words
my_lexicon <- update_key(my_lexicon,
  x = data.frame(
    x = c("awesome", "terrible"),
    y = c(1, -1)
  )
)

# Use custom lexicon
sentiment(text, polarity_dt = my_lexicon)

Valence Shifter Tables

# View default valence shifters
lexicon::hash_valence_shifters

# Custom valence shifters
my_shifters <- update_key(
  lexicon::hash_valence_shifters,
  x = data.frame(
    x = c("kinda", "sorta"),
    y = c(2, 2)  # 2 = de-amplifier
  )
)

sentiment(text, valence_shifters_dt = my_shifters)