Analyze Text Sentiment Across Multiple Categories

Go beyond basic sentiment analysis. Uncover nuanced customer feedback by assigning precise sentiment scores to specific product or service categories.

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    Workflow Overview

    What is this?

    What is this?

    This workflow provides a powerful AI-driven sentiment analysis engine. It processes any text input and returns a structured JSON output, identifying sentiment as positive, negative, or neutral, and can even break down sentiment across multiple, user-defined categories like 'price', 'service', or 'quality'.
    What problem does it solve?

    What problem does it solve?

    Are you struggling to understand the nuances in customer reviews or survey feedback? This tool automates the process of sifting through text, saving you from manual analysis and providing detailed insights into exactly what aspects of your business customers are happy or unhappy with.
    What will you get?

    What will you get?

    You will get a tool that can instantly analyze customer feedback for deep insights, automate the process of tagging and categorizing qualitative data, and generate structured, machine-readable sentiment data for dashboards or further analysis. This allows for quick, data-driven decisions to improve your products and services.

    Apps Included

    • Sticky Note
    • If
    • OpenAI
    • Start

    How to Use

    Prerequisites

    Setup Steps

    1

    Import the Workflow

    Import this workflow into your Dify account. The application is pre-configured and ready to use.

    2

    Run the Application

    Navigate to the application's main page and input the text you want to analyze in the 'input_text' field.

    3

    Configure Analysis Mode

    Choose the analysis mode using the 'Multisentiment' dropdown. Select 'False' for a detailed, category-by-category breakdown, or 'True' for a single, overall sentiment score for the entire text.

    4

    Define Categories (Optional)

    If you chose the multi-sentiment mode, you can provide a comma-separated list of categories (e.g., 'quality, service, price') in the 'Categories' field to guide the AI's analysis. If left blank, the AI will attempt to determine relevant categories automatically.

    5

    Execute and View Results

    Click the run button. The workflow will process the input and return a clean JSON object containing the sentiment analysis, including scores and relevant keywords.

    Pro Tips

    1
    For batch processing, use the Dify API to programmatically send this workflow text and store the resulting JSON in a database for trend analysis over time.
    2
    Experiment with the system prompt inside the LLM nodes to fine-tune the output format or add more analytical dimensions, such as emotion detection or intent classification.
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    Information

    • Published date8/15/2025
    • Last updated8/15/2025

    Platform

    Tags

    Scenes
    Difficulty