Student Sentiment Analysis Platform
Korean sentiment analysis system for educational feedback with network visualization
Overview
Developed a comprehensive Korean text mining platform for analyzing student feedback and educational content, featuring advanced sentiment analysis and interactive network visualizations.
Key Features
- Korean Text Mining: Comprehensive pipeline for Korean educational text processing
- Network Analysis: Word co-occurrence networks and interactive visualizations
- Automated Categorization: System for identifying and categorizing student concerns
- Interactive Visualizations: Dynamic HTML-based network graphs and charts
Technical Implementation
- Text Processing: Korean morphological analysis using KoNLPy
- Network Analysis: Word frequency and co-occurrence analysis with NetworkX
- Visualization: Interactive network graphs and statistical charts
- Data Pipeline: Automated text cleaning, processing, and analysis workflow
Technologies Used
- Korean NLP: KoNLPy (Okt), morphological analysis
- Network Analysis: NetworkX, interactive graph generation
- Visualization: Matplotlib, interactive HTML visualizations
- Data Processing: Pandas, statistical analysis, pattern discovery
Applications
- Student feedback analysis for educational improvement
- Automated concern detection and categorization
- Educational content sentiment monitoring
- Real-time text analysis for educational platforms
Impact
Provided actionable insights for educational content improvement and student experience enhancement through automated Korean text analysis.