https://github.com/jtperez-acle/rocket-portfolio
Rocket framework portfolio; written in Rust
https://github.com/jtperez-acle/rocket-portfolio
Last synced: 2 months ago
JSON representation
Rocket framework portfolio; written in Rust
- Host: GitHub
- URL: https://github.com/jtperez-acle/rocket-portfolio
- Owner: JtPerez-Acle
- Created: 2024-01-23T14:00:12.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-23T21:59:47.000Z (over 1 year ago)
- Last Synced: 2025-02-07T13:30:04.239Z (4 months ago)
- Language: JavaScript
- Size: 201 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Project Description for Social Media Sentiment Analysis Tool
The Social Media Sentiment Analysis Tool (SMSAL) is an advanced, data-driven web application designed to analyze and visualize the sentiment of social media posts across platforms (initialy one). This tool leverages the power of Natural Language Processing (NLP) and sentiment analysis algorithms to process large volumes of social media data, providing real-time insights into public opinion and trends.
Features
**Real-Time Data Analysis**: The tool continuously fetches and analyzes social media posts, offering up-to-date sentiment analysis.
**Multi-Platform Support**: Seamlessly integrates with various social media platforms such as Twitter, Facebook, and Instagram.
**Sentiment Score Calculation**: Utilizes NLP techniques to assign sentiment scores to posts, categorizing them as positive, negative, or neutral.
**Interactive Dashboard**: A user-friendly dashboard displays sentiment trends, frequency of mentions, and other key metrics in an easily digestible format.
**Data Export Options**: Allows users to export the analyzed data for further use or reporting.
**Responsive Design**: Ensures a seamless experience across all devices, including mobiles and tablets.
Technologies
**Frontend**: React.js for dynamic UI, complemented by HTML, CSS, and JavaScript.
**Backend**: Rust with Rocket framework, ensuring high performance and safety.
**Data Analysis**: Python-based sentiment analysis libraries and APIs.
**Database**: SQL or NoSQL database for storing analyzed data.
**Deployment**: Containerized using Docker and deployable on any cloud platform.
Potential Use Cases
**Market Research**: Businesses can gauge public reaction to products or campaigns.
**Public Opinion Tracking**: For monitoring social issues or political campaigns.
**Content Strategy**: Assisting social media managers and content creators in understanding audience reception.
Goals and Future Enhancements
Initially, the project aims to accurately analyze and display sentiment trends.
Future enhancements could include predictive analytics, broader platform integration, and advanced filtering options.
Contributing
This project is part of my personal portfolio and intentions of improving the quality of life of people around the world.