Sentiments Docs
Fall 2025
API

# o1.sentiment

package o1.sentiment

## Members list

### Packages

package o1.sentiment.ui

### Type members

#### Classlikes

class SentimentAnalyzer

An instance of this class is a “sentiment analyzer” taught on a corpus of texts whose sentiments have been appraised and annotated by a human. Given a roughly similar piece of text as those that appear in its training data, the analyzer can assign the text a numerical rating that reflects how positive or negative it is; see the rate method.

An instance of this class is a “sentiment analyzer” taught on a corpus of texts whose sentiments have been appraised and annotated by a human. Given a roughly similar piece of text as those that appear in its training data, the analyzer can assign the text a numerical rating that reflects how positive or negative it is; see the rate method.

The `SentimentAnalyzer` companion object provides methods for initializing analyzer objects from training data.

## Attributes

Companion
  object
Supertypes
  class Object
  trait Matchable
  class Any

object SentimentAnalyzer

This companion object of class SentimentAnalyzer provides methods for initializing analyzer instances from training data.

This companion object of class SentimentAnalyzer provides methods for initializing analyzer instances from training data.

The methods expect the data to be in the following line-based format:

    -1 Aggressive self-glorification and a manipulative whitewash.
    2 A comedy-drama of nearly epic proportions rooted in a sincere performance by the title character undergoing midlife crisis.
    -1 Narratively, Trouble Every Day is a plodding mess.
    1 The Importance of Being Earnest, so thick with wit it plays like a reading from Bartlett's Familiar Quotations
    0 It's everything you'd expect -- but nothing more.

That is, each line of input should start with a sentiment rating of -2, -1, 0, 1, 2. A negative numbers means that the rest of the line expresses a negative sentiment, as determined by a human rater; positive numbers correspondingly reflect positive sentiments.

## Attributes

Companion
  class
Supertypes
  class Object
  trait Matchable
  class Any
Self type
  SentimentAnalyzer.type

### Value members

#### Concrete methods

def cleanText(`text`: String): String

Cleans the given line of text for use by a SentimentAnalyzer: normalizes apostrophes and whitespace and discards unwanted punctuation.

Cleans the given line of text for use by a SentimentAnalyzer: normalizes apostrophes and whitespace and discards unwanted punctuation.

## Attributes