https://github.com/tanmay-chandgude/quantify
A dynamic analytics module that leverages DataStax Astra DB and Langflow to analyze and provide insights on social media engagement data.
https://github.com/tanmay-chandgude/quantify
astradb datastax gpt-4 langflow model social-media typescript
Last synced: 3 months ago
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A dynamic analytics module that leverages DataStax Astra DB and Langflow to analyze and provide insights on social media engagement data.
- Host: GitHub
- URL: https://github.com/tanmay-chandgude/quantify
- Owner: Tanmay-Chandgude
- Created: 2025-01-06T18:07:09.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-07T09:42:31.000Z (5 months ago)
- Last Synced: 2025-01-07T10:35:51.052Z (5 months ago)
- Topics: astradb, datastax, gpt-4, langflow, model, social-media, typescript
- Language: TypeScript
- Homepage:
- Size: 68.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# **Quantify**
Analyze and visualize engagement metrics for social media posts using advanced analytics and data visualization techniques.
---
## **Table of Contents**
- [Project Overview](#project-overview)
- [Features](#features)
- [Tech Stack](#tech-stack)
- [Dataset](#dataset)
- [Installation](#installation)
- [Usage](#usage)
- [Screenshots](#screenshots)
- [Contributing](#contributing)
- [License](#license)
- [Acknowledgments](#acknowledgments)
---
## **Project Overview**
Quantify provides actionable insights into social media engagement data. This project utilizes a mock dataset of social media posts, allowing you to:
- Analyze post performance.
- Understand engagement patterns across platforms.
- Extract valuable insights for optimizing social media strategies.
---
## **Features**
### Engagement Metrics
- Analyze likes, comments, shares, saves, and views for each post.
### Sentiment Analysis
- Evaluate post comments' sentiment (positive, neutral, negative).
### User Demographics
- Understand engagement patterns across age groups, genders, and locations.
### Platform Insights
- Compare performance across Instagram, Facebook, and Twitter.
### Hashtag Effectiveness
- Discover the impact of hashtags on engagement rates.
### Temporal Trends
- Identify peak engagement times and optimize posting schedules.
---
## **Tech Stack**
- **Frontend**: React.js (TypeScript), Vite, TailwindCSS
- **Backend**: Node.js, Express.js
- **Database**: DataStax Astra DB
- **AI Analytics**: Langflow with GPT Integration
- **Visualization**: Chart.js, Recharts
- **File Parsing**: Papa Parse
---
## **Dataset**
The mock dataset includes:
- **Post Details**: Type, content length, hashtags.
- **Engagement Metrics**: Likes, comments, shares, saves.
- **User Info**: Age, gender, location.
- **Sentiment Analysis**: Positive, neutral, negative.
- **Platform and Time Trends**: Platform-specific and peak times.
---
## **Installation**
1. Clone the repository:
```bash
git clone https://github.com/your-username/quantify.git
cd Quantify
```
2. Install dependencies:
```bash
npm install
```
3. Set up the database:
- Create an account on [DataStax Astra DB](https://www.datastax.com/astra).
- Obtain credentials and update the `.env` file.
4. Start the development server:
```bash
npm start
```
---
## **Usage**
1. Upload a CSV dataset through the app's interface.
2. Explore insights with:
- Visualized metrics and trends.
- Sentiment and demographic analysis.
- Comparison across platforms.
---
## **Contributing**
Contributions are welcome! Please follow these steps:
1. Fork the repository.
2. Create a new branch:
```bash
git checkout -b feature-name
```
3. Commit your changes:
```bash
git commit -m "Add feature-name"
```
4. Push and open a pull request.
---
## **License**
This project is licensed under the [MIT License](LICENSE).
---
## **Acknowledgments**
Special thanks to:
- [Langflow](https://langflow.org) for AI capabilities.
- [DataStax Astra DB](https://www.datastax.com/astra) for database support.
- Open-source libraries and the developer community.
```