n8n-nodes-marlo-sentiment

This is an n8n community node that integrates with the Marlo Sentiment Analysis API via RapidAPI to perform AI-powered sentiment analysis on text content.

Prerequisites

You need the following installed on your development machine:

• git
• Node.js and npm. Minimum version Node 20. You can find instructions on how to install both here.
• Install n8n with:

  npm install n8n -g

Installation

Community Nodes (Recommended)

For users on n8n v0.187+, your instance owner can install this node from Settings > Community Nodes.

The installation identifier is:

n8n-nodes-marlo-sentiment

Manual Installation

To install the node locally, you can use n8n's community node installation feature:

cd ~/.n8n && npm install n8n-nodes-marlo-sentiment

For Docker users, add the following line before the font installation command in your n8n Dockerfile:

RUN cd /usr/local/lib/node_modules/n8n && npm install n8n-nodes-marlo-sentiment

Restart n8n and you should see the Marlo Sentiment node available in the nodes panel.

Configuration

Credentials

Before using this node, you need to configure your RapidAPI credentials:

1. Get RapidAPI Access: Visit the Marlo Sentiment API on RapidAPI
2. Subscribe: Subscribe to the API plan that fits your needs
3. Get API Key: Copy your RapidAPI key from the dashboard
4. Configure in n8n:
   • In n8n, create new credentials for "Marlo Sentiment API"
   • Enter your RapidAPI key
   • The RapidAPI Host should be: marlo-sentiment.p.rapidapi.com

Operations

Analyze Sentiment

Analyzes the sentiment of text content and returns:

• Sentiment: Overall sentiment classification (positive, negative, neutral)
• Confidence: Confidence score for the sentiment classification (0-1)
• Text Length: Character count of the analyzed text
• Industry Context (optional): Industry-specific sentiment analysis
• Raw Scores (optional): Detailed sentiment scores (positive, negative, neutral, compound)

Supported Industries

The node supports industry-specific sentiment analysis for:

• Healthcare
• Technology
• Gaming
• Finance
• Restaurant
• Automotive
• Real Estate
• Fitness
• Education
• Retail

Usage Examples

Basic Sentiment Analysis

1. Add the Marlo Sentiment node to your workflow
2. Configure your credentials
3. Set the Text parameter to the content you want to analyze
4. The node will return sentiment analysis results

Industry-Specific Analysis

1. Configure the node as above
2. Set the Industry parameter to match your content context
3. This provides more accurate sentiment analysis for industry-specific language

Batch Processing

The node can process multiple items in a workflow, making it perfect for:

• Analyzing customer feedback from surveys
• Processing social media mentions
• Evaluating product reviews
• Monitoring support ticket sentiment

Node Parameters

| Parameter | Type | Required | Description | |-----------|------|----------|-------------| | Text | String | Yes | The text content to analyze for sentiment | | Industry | Options | No | Industry context for more accurate analysis | | Include Raw Scores | Boolean | No | Whether to include detailed sentiment scores in output |

Output

The node outputs a JSON object with the following structure:

{
  "sentiment": "positive",
  "confidence": 0.85,
  "text_length": 150,
  "original_text": "Your analyzed text...",
  "industry": "technology",
  "scores": {
    "positive": 0.8,
    "negative": 0.1,
    "neutral": 0.1,
    "compound": 0.75
  }
}

Error Handling

The node includes comprehensive error handling:

• Empty text: Returns an error if no text is provided
• API errors: Handles RapidAPI rate limits and authentication errors
• Network issues: Gracefully handles connection problems
• Continue on fail: Option to continue workflow execution even if sentiment analysis fails

Resources

• n8n community nodes documentation
• Marlo Sentiment API Documentation
• Marlo Cloud Official Website

Version History

1.0.0

• Initial release
• Basic sentiment analysis functionality
• Industry-specific analysis support
• RapidAPI integration
• Comprehensive error handling

License

MIT