Computational Social Sciences
Analyzing Human Interaction: From Digital Humanities to Urban Network Modeling.
Quantifying the Social Fabric
Social phenomena are no longer purely qualitative. Malgukke provides the computational power required to process massive text corpora, model complex urban migrations, and analyze the dynamics of global financial markets through Large Language Models (LLM) and graph-based network analysis.
Digital Humanities
Text Mining: LLM-based analysis of historical archives spanning centuries.
Image Recognition: Using computer vision to catalog and analyze artistic patterns in global museum databases.
Economics & Markets
Market Simulation: Running Monte Carlo simulations for high-frequency trading and risk assessment.
Big Data Economics: Analyzing real-time consumer behavior across global digital platforms.
Sociology & Networks
Social Network Analysis: Graph-based modeling of information spread and opinion dynamics.
Migration Flows: Simulating population movements using large-scale mobility datasets.
Urban Planning & Smart Cities
Infrastructure Modeling: Simulating traffic flow and public transport efficiency in megacities.
Resource Distribution: Optimizing utility networks based on predictive demographic shifts.
Social Logic: Data Source -> Methodology -> Societal Insight
| Domain | Compute Methodology | Research Insight |
|---|---|---|
| Linguistics | Fine-tuning Transformer models on 100TB+ multilingual text data. | Evolution of Language Patterns |
| Finance | Agent-based modeling (ABM) to predict systemic market collapses. | Enhanced Economic Stability |
| Urban Development | Spatiotemporal clustering of mobile positioning data. | Optimized Urban Logistics |