Social Media Analytics

 

BSc IT Project Guide: Social Media Analytics

1. Project Title

Social Media Analytics to Monitor Live Social Media Trends and Engagement

2. Objective

To design and develop a web-based platform that monitors live social media activity, analyzes engagement metrics (likes, shares, comments), and visualizes trends using real-time data.

3. Scope

The system will support data aggregation from platforms such as Twitter and Instagram, perform sentiment analysis, and present user-friendly dashboards to monitor engagement and trending topics.

4. Tools and Technologies

- Frontend: HTML, CSS, JavaScript (React or Vue.js)
- Backend: Python (Flask/Django)
- APIs: Twitter API, Instagram Graph API
- Database: MongoDB / PostgreSQL
- Data Visualization: Chart.js / D3.js / Plotly
- Sentiment Analysis: TextBlob / VADER / Transformers (HuggingFace)
- Real-Time Processing: WebSockets / Firebase / Apache Kafka

5. Functional Requirements

- User authentication and access control
- API integration to fetch social media data
- Real-time sentiment analysis and keyword extraction
- Dashboards for metrics: likes, retweets, shares, etc.
- Trending hashtags and influencer analysis
- Historical data storage and querying

6. Non-Functional Requirements

- Responsive UI
- Secure API access and data encryption
- Scalability to support large data inflow
- High availability and minimal latency

7. Project Development Phases

1. Requirement Gathering
2. System Design and Planning
3. API Integration and Backend Setup
4. Frontend Development and Visualization
5. Sentiment Analysis Integration
6. Testing and Debugging
7. Deployment and Documentation

8. Expected Outcome

A fully functional social media analytics dashboard capable of tracking real-time trends, performing sentiment analysis, and displaying metrics in a comprehensive and interactive way.

9. Conclusion

This project helps students explore concepts in real-time data processing, data analytics, and full-stack web development, providing insights into how modern systems track public engagement and sentiment across social platforms.