Sentiment Evaluator

The SentimentEvaluator analyzes the emotional tone of a given text, typically classifying it as positive, negative, or neutral. It can also provide a numerical score indicating the intensity of the sentiment. This is useful for ensuring agents maintain an appropriate tone or for flagging overly negative or positive responses. Experience shows this is a good first-pass check for agent demeanor.

It usually relies on pre-trained sentiment analysis models or libraries (like VADER, AFINN, or others).

Core Workflow

The SentimentEvaluator processes an input text (e.g., an agent's response) using an underlying sentiment analysis engine or library. This analysis typically yields a categorical classification (like positive, negative, or neutral) and/or a numerical sentiment score. These findings are then reported in the EvaluationResult.

Use Cases

The SentimentEvaluator is helpful for:

• Monitoring the overall tone of agent responses (e.g., ensuring helpfulness, avoiding aggression).
• Flagging customer interactions that may require human review due to strong negative sentiment.
• Analyzing user feedback for emotional content.
• Ensuring marketing copy or agent personas align with desired sentiment profiles.

Configuration

Configuration might involve:

• sourceField: Specifies which field from EvaluationInput to analyze (defaults to 'response').
• Potentially, selecting a specific sentiment analysis model or library if multiple are supported, or passing parameters to the underlying library.

// Example configuration structure (to be detailed)
// {
//   type: 'Sentiment',
//   sourceField: 'response.text',
//   // modelConfig: { /* optional: specify model or library params */ }
// }

Output (EvaluationResult)

The SentimentEvaluator produces an EvaluationResult:

• criterionName: Reflects the sentiment check (e.g., "ResponseSentiment").
• score: Can be a categorical label (e.g., "positive", "negative", "neutral") or a numeric score (e.g., a value from -1 to 1).
• reasoning: Might include the raw numeric score if the main score is categorical, or a list of words that most influenced the sentiment.
• evaluatorType: 'Sentiment'.
• error: For issues accessing the text or problems with the sentiment analysis engine.

This evaluator provides a quick way to gauge the emotional tone of text, an important factor in human-agent interaction.