Showcase/Sentiment Analysis
beginnertext

Sentiment Analysis

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

📝

text annotation

Configuration Fileconfig.yaml

# Sentiment Analysis Configuration
# Generated by Potato Annotation Showcase

port: 8000
server_name: localhost
task_name: "Sentiment Analysis"

# Data configuration
data_files:
  - data.json
id_key: id
text_key: text

# Output
output_file: annotations.json

# Annotation scheme
annotation_schemes:
  - annotation_type: radio
    name: sentiment
    description: "What is the sentiment expressed in this text?"
    labels:
      - Positive
      - Negative
      - Neutral
    keyboard_shortcuts:
      Positive: "1"
      Negative: "2"
      Neutral: "3"
    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
allow_all_users: true

# Task assignment
instances_per_annotator: 100
annotation_per_instance: 1

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 items

Get This Design

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

radio

Domain

NLPSocial Media

Use Cases

Sentiment AnalysisText Classification

Tags

sentimentclassificationtwitterreviews

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