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# TN-hackathon | ||
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Only nessary data | ||
This project was developed for TN Police 2023 conducted at St. Joseph College, Chennai, addressing the problem statement of social media analysis (YouTube). | ||
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## Problem Statement | ||
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The objective was to analyze YouTube data to provide insights into comment sentiment, uploader location, and video content. | ||
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## Features | ||
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- **Comment Analysis**: Analyze sentiment and content of comments on YouTube videos. | ||
- **Uploader Location**: Determine the geographical location of video uploaders based on metadata. | ||
- **Video Analysis**: Extract insights from video content such as tags, categories, and key themes. | ||
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## Components | ||
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### 1. AI Model | ||
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Describe the AI model(s) used for: | ||
- Sentiment analysis of comments. | ||
- Geolocation extraction from uploader data. | ||
- Video content analysis. | ||
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### 2. Backend | ||
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The backend is responsible for: | ||
- Integrating with YouTube API for data retrieval. | ||
- Implementing data processing and analysis algorithms. | ||
- Exposing APIs for frontend and external access using DRF. | ||
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### 3. Frontend | ||
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The frontend provides: | ||
- Made with React | ||
- User interface to interact with analyzed data. | ||
- Visualization of insights and analytics generated by the backend. | ||
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