Sentiment Analysis
Simple 3-way sentiment classification with radio buttons. Perfect for social media analysis, product reviews, and customer feedback.

Configuration Fileconfig.yaml
# Sentiment Analysis Configuration
# Generated by Potato Annotation Showcase
port: 8000
annotation_task_name: "Sentiment Analysis"
task_dir: "."
# Data configuration
data_files:
- "data.json"
item_properties:
id_key: id
text_key: text
# Output
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"
# Annotation scheme
annotation_schemes:
- annotation_type: radio
name: sentiment
description: "What is the sentiment expressed in this text?"
labels:
- name: Positive
key_value: "1"
- name: Negative
key_value: "2"
- name: Neutral
key_value: "3"
sequential_key_binding: true
tooltips:
Positive: "The text expresses happiness, satisfaction, approval, or other positive emotions"
Negative: "The text expresses sadness, anger, frustration, disappointment, or other negative emotions"
Neutral: "The text does not express strong positive or negative sentiment, or is purely factual"
# User configuration
require_password: false
# Task assignment
Sample Datasample-data.json
[
{
"id": "sample_1",
"text": "I absolutely love this product! It exceeded all my expectations and I would highly recommend it to everyone."
},
{
"id": "sample_2",
"text": "The service was terrible. I waited for hours and nobody helped me. Very disappointed."
}
]
// ... and 1 more itemsTry it live — no install
Boot the real Potato server in your browser (WebAssembly) and annotate with this exact config. Nothing leaves your machine.
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This design is available in our showcase. Copy the configuration below to get started.
Quick start:
# Create your project folder mkdir sentiment-analysis cd sentiment-analysis # Copy config.yaml from above potato start config.yaml
Details
Annotation Types
Domain
Use Cases
Tags
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