Machine Learning in the Social Sciences

• Natural Language Processing (NLP)
  • Domain Specific Large Language Models for Sociology
    • Establishing evaluation benchmarks for domain-specific ML tasks
    • Transfer learning and model optimization using domain knowledge
    • Fine-tuning transformer models for social science applications
    • Identifying and addressing biases in pre-trained models

• Social Network Analysis (SNA)
  • Semantic Similarity Graphs
    • Extraction of latent semantic structures in the discourse on social inequality
  • Combining SNA and NLP approaches