https://github.com/itprodirect/ml-ytvibes-commentanalyzer

YouTube comment analyzer application - find out what the vibes are in the comments by looking at data visualizations
https://github.com/itprodirect/ml-ytvibes-commentanalyzer

Last synced: about 1 year ago
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YouTube comment analyzer application - find out what the vibes are in the comments by looking at data visualizations

• Host: GitHub
• URL: https://github.com/itprodirect/ml-ytvibes-commentanalyzer
• Owner: itprodirect
• Created: 2023-09-16T02:05:11.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2023-09-19T02:36:17.000Z (almost 3 years ago)
• Last Synced: 2025-05-18T22:14:18.586Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 967 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 📊 ML-YTVibes-CommentAnalyzer

ML-YTVibes-CommentAnalyzer is a Python application designed to **analyze the sentiments** of comments on a YouTube video and provide **insights into the emotions** expressed by viewers.

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## 🌟 Introduction

Understanding the sentiments of YouTube viewers can be crucial for content creators and marketers. This application provides a simple yet powerful way to gauge the emotional response of the audience to a video, helping creators and analysts make data-driven decisions.

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## 🎯 Features

- **🔍 Sentiment Analysis**: Uses NLP to analyze the sentiments of comments.

- **📊 Sentiment Visualization**: Interactive histograms and scatter plots to visualize sentiments.

- **📝 Comment Length Analysis**: Relates comment length to sentiment.

- **☁️ Word Cloud Generation**: Identifies most frequently used words in comments.

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## 📈 Visualizations

### 📌 Word Cloud of Frequent and Interesting Words

![YT Comment Frequent Interesting Word Cloud](screenshots/YT_comment_frequent_interesting_word_cloud.png)

_Description: Shows the most frequent and interesting words appearing in YouTube comments._

### 📌 Comment Length and Frequency Bar Chart

![YT Comment Length and Frequency Bar Chart](screenshots/YT_comment_length__and_frequency_barchart.png)

_Description: Displays the frequency of different comment lengths._

### 📌 Comment Length Distribution Bar Chart

![YT Comment Length Distribution Bar Chart](screenshots/YT_comment_length_distribution_barchart.png)

_Description: Distribution of comment lengths on a YouTube video._

### 📌 Vibe Check Bar Chart

![YT Comment Vibe Check Bar Chart](screenshots/YT_comment_vibe_check_barchart.png)

_Description: Sentiment analysis categorized as positive, negative, or neutral._

### 📌 Vibe Scatter Plot

![YT Comment Vibe Scatter Plot](screenshots/YT_comment_vibe_scatterplot.png)

_Description: Scatter plot showing the relationship between comment length and sentiment._

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## 🚀 Getting Started

1. **Clone or download** this repository to your local machine.

2. Ensure you have **Python** installed on your system (Python 3.x recommended).

3. Install the required Python libraries by running the following command:

   ```bash

   pip install -r requirements.txt