NLP & Semantic Network Analysis

Jan 10, 2026 · 1 min read
projects

This project is the technical implementation behind the publication “A Multi-Method Validation Framework for Large-Scale Multilingual Text Analytics” (JADT 2026, in review). It operationalizes the full analytical workflow used in the paper, from data preparation to cross-method validation and result comparison.

The pipeline combines R and Python modules over a large multilingual review corpus, including: preprocessing and TF-IDF, LDA topic modeling, LSA and Correspondence Analysis, lexicon- and model-based sentiment analysis, clustering, and co-occurrence network analysis. The repository also includes cross-platform validation scripts to compare method outputs and check structural stability across implementations.

The central objective is methodological robustness: verifying which findings remain consistent when methods, model families, and language-specific components vary. In this sense, the project is not a generic NLP demo, but a reproducible research pipeline designed for quantitative validation of text-analytic conclusions.

Research Text Mining Network Science Correspondence Analysis Clustering R
Stefano Blando
Authors
Stefano Blando (he/him)
PhD Student in Artificial Intelligence
Stefano Blando is a PhD student in the National PhD Program in Artificial Intelligence at Scuola Superiore Sant’Anna and the University of Pisa. His research lies at the intersection of AI, agent-based modeling, and economics. He studies adaptive multi-agent systems, statistical verification of economic simulations, and robust quantitative methods for financial and socio-economic data.