https://github.com/balaji1233/youtube-comment-sentiment-insights
This project delivers a robust web application that conducts potent sentiment analysis on YouTube comments.
https://github.com/balaji1233/youtube-comment-sentiment-insights
flask nltk-library python streamlit youtube-api
Last synced: 2 months ago
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This project delivers a robust web application that conducts potent sentiment analysis on YouTube comments.
- Host: GitHub
- URL: https://github.com/balaji1233/youtube-comment-sentiment-insights
- Owner: balaji1233
- Created: 2023-12-04T10:35:47.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-12-04T13:37:13.000Z (almost 2 years ago)
- Last Synced: 2025-03-19T17:09:42.256Z (7 months ago)
- Topics: flask, nltk-library, python, streamlit, youtube-api
- Language: Python
- Homepage:
- Size: 26.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# YouTube Sentiment Analysis 👍👎😊
This project introduces a dynamic web application that performs rigorous sentiment analysis on YouTube comments. Users can submit a YouTube link, and the application scrutinizes the sentiment of the associated comments. Additionally, it exhibits video details, channel specifics, and graphical representations of the sentiment analysis outcomes.
## Features ✨
-Derives the video ID from a given YouTube link.
-Harvests comments from the designated YouTube video and archives them in a CSV file. 💬📑
-Executes sentiment analysis on the comments utilizing the VADER (Valence Aware Dictionary and sEntiment
Reasoner) sentiment analysis instrument. 😃😠😐
-Fabricates bar charts and scatter plots to illustrate the sentiment analysis findings. 📊📈
-Procures video and channel specifics from the YouTube API. 📺🔍
-Offers an interactive web interface via Streamlit. 🌐✨
## Installation 🛠️
1. Clone the repository:
2. Install the required dependencies:
3. Obtain a YouTube Data API key from the [Google Cloud Console](https://console.cloud.google.com/) and replace `YOUR_API_KEY` in `YoutubeCommentScrapper.py` with your actual API key.
4. Run the application:
## Usage 🚀
1. Open the application in your web browser.
2. Enter a valid YouTube link in the sidebar. 🔗
3. Wait for the application to retrieve the video and channel information, save the comments to a CSV file, perform sentiment analysis, and display the results. ⌛
4. Explore the sentiment analysis results, video information, and channel information. 📈📺