Computational Resources
NSF ACCESS Computing
- High-performance computing allocation for large-scale text analysis
- GPU resources for machine learning model training
- Storage for large datasets (protest events, media archives)
- Python: pandas, scikit-learn, spaCy, networkx
- R: tidyverse, quanteda, igraph, ggplot2
- GIS: QGIS, ArcGIS, PostGIS, leaflet
- Qualitative: NVivo, Atlas.ti, Dedoose
Data Sources
Primary Archives
- Times of India digital archives (1990-present)
- Government of India statistical databases
- Social media APIs (Twitter, Facebook, YouTube)
- Academic protest event datasets
Specialized Collections
- South Asian newspaper collections
- NGO reports and documentation
- Government white papers and policy documents
- Academic literature databases
Training Programs
Computational Methods Workshop Series
- Introduction to Python for social science research
- Text analysis and natural language processing
- Network analysis and visualization
- Machine learning for social scientists
Research Skills Development
- Literature review and bibliography management
- Data visualization and presentation
- Academic writing and collaboration
- Conference presentation skills
Lab Infrastructure
Physical Space
- Dedicated research workspace with multiple monitors
- Collaborative meeting and presentation area
- Secure storage for sensitive data
- High-speed internet and computing resources
Remote Collaboration
- Slack workspace for team communication
- GitHub organization for code sharing
- Shared cloud storage for project materials
- Video conferencing setup for virtual meetings
Getting Involved
Interested students should contact Prof. Sorge about:
- Independent study opportunities
- Summer research positions
- Senior thesis collaboration
- Graduate school preparation