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Research project

Gendered body language and speech styles in UK Parliament using machine learning

Project overview

This project aimed at studying how gender mediate body language and speech styles in Parliamentary debates, using methodological and empirical contributions to both fields. We developed tools to study audio in Parliamentary debates from the House of Commons and used methods from Natural Language Technique to extract information from Hansard transcripts.

Staff

Lead researcher

Dr Rafael Mestre PhD, MSc, BSc

New Frontiers Fellow

Research interests

  • Responsible Research and Innovation of emergent technologies
  • Multimodal machine learning and Natural Language Processing
  • Computational social science

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Other researchers

Dr Stuart Middleton

Associate Professor

Research interests

  • Natural Language Processing
  • Human-in-the-loop NLP: Active Learning, Adversarial Training, Rationale-based Learning, Interactive Sense Making
  • Information Extraction: Few/Zero Shot Learning, Graph-based Models, Behaviour Classification, Geoparsing/Location Extraction, Event Extraction, Argument Mining

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Dr Matt Ryan

Associate Professor

Research interests

  • Democracy
  • Social Research Methods
  • Web Science

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Professor Tim Norman

Head of School

Research interests

  • Learning and reasoning under uncertainty
  • AI safety
  • Human-AI collaboration

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