textblob-sentiment

Name: textblob-sentiment
Availability: InStock
Author: DTMC-marketplace

Analyze text polarity and subjectivity using the TextBlob library.

2|Updated Jan 15, 2026

Search Tags:#nlp #text processing #sentiment analysis #textblob #societal #opinion mining

Ready to run

npx skills add https://github.com/DTMC-marketplace/governance --skill textblob-sentiment

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: textblob-sentiment
Source: https://github.com/DTMC-marketplace/governance/tree/main/skills/textblob-sentiment
Command: npx skills add https://github.com/DTMC-marketplace/governance --skill textblob-sentiment

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the need to quickly understand the emotional tone and subjective nature of text data, which is crucial for monitoring user feedback, social media sentiment, and content analysis.

Core Features & Use Cases

Sentiment Polarity: Determine if text is positive, negative, or neutral.
Subjectivity Analysis: Gauge how opinionated or factual a piece of text is.
Use Case: Analyze customer reviews to identify common complaints or positive feedback trends, enabling targeted improvements to products or services.

Quick Start

Use the textblob-sentiment skill to analyze the sentiment of the following text: "This is a fantastic product, I love it!".

Frequently Asked Questions about textblob-sentiment

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze text sentiment for customer feedback?▼

To analyze text sentiment for customer feedback, this Skill uses the TextBlob library to process natural language and output polarity and subjectivity scores, identifying positive, negative, or neutral emotional tones.

What is subjectivity analysis in natural language processing?▼

Subjectivity analysis gauges how opinionated or factual a piece of text is. This Skill evaluates textual data using the TextBlob library to output a subjectivity score alongside sentiment polarity for content analysis.

Can I use TextBlob for social media monitoring?▼

Yes, you can use TextBlob for social media monitoring. This Skill applies TextBlob sentiment analysis to process natural language from social posts, outputting polarity scores to track public opinion and emotional trends.

How do I determine if text is positive or negative using NLP?▼

To determine if text is positive or negative using NLP, this Skill calculates sentiment polarity via the TextBlob library. It processes your textual data and outputs scores indicating whether the emotional tone is positive, negative, or neutral.

What are the limitations of TextBlob for opinion mining?▼

TextBlob for opinion mining provides basic sentiment polarity and subjectivity scores. As a basic implementation, it processes natural language text directly but may lack deep contextual reasoning for complex content moderation or nuanced sentiment analysis tasks.