Text Analytics and Language Models
I apply text analytics and language models to multilingual corpora, sentiment and narrative dynamics, and to systems based on retrieval and embeddings.
- NLP
- Narrative Economics
- Foundation Models
I apply text analytics methods and language models to the study of unstructured data. The work covers the semantic structure of multilingual corpora, the extraction of sentiment and narrative dynamics, and the construction of systems based on retrieval, custom embeddings, and parameter-efficient adaptation of pretrained models. I use classical text analytics alongside transformer architectures, state-space models, and foundation models, with attention to verifying that results depend on the data rather than on the technique employed.
Publications
- A Multi-Method Validation Framework for Large-Scale Multilingual Text Analytics Presented at JADT 2026 and awarded the VADISTAT Prize for young researchers, this paper validates 18 analytical approaches on 1M+ texts to identify method-invariant findings.
- NLP
- Methodology
- BERT
- Graph Neural Networks
Projects
- Lightweight Fine-Tuning with PEFT & LoRA Parameter-efficient fine-tuning pipeline using LoRA to adapt DistilBERT for sentiment analysis while training less than 1% of the model parameters.
- Side Quest
- Generative AI
- NLP
- PEFT / LoRA
- NLP & Semantic Network Analysis Technical implementation of the JADT paper pipeline, integrating multilingual preprocessing, topic modeling, correspondence analysis, semantic spaces, sentiment modules, and network-based validation across methods.
- Research
- Text Mining
- Network Science
- Correspondence Analysis
- Custom Chatbot with RAG Retrieval-augmented chatbot that combines semantic search, custom embeddings, and LLM prompting for grounded domain-specific conversations.
- Side Quest
- Generative AI
- NLP
- RAG