Research project

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

Lead researchers:

Dr Rafael Mestre,

Dr Jessica Smith
Other researchers:

Dr Stuart Middleton,

Professor Matt Ryan,

Professor Tim Norman
Status:

Not active

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 researchers

Dr Rafael Mestre PhD, MSc, BSc

Lecturer

Research interests

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

Connect with Rafael

Email: [email protected]

Dr Jessica Smith

Lecturer in Politics & International Rel

Research interests

Political behaviour and gender-based stereotyping
Executive politics
British politics

Connect with Jessica

Email: [email protected]

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

Connect with Stuart

Email: [email protected]