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Research project

SafeSpacesNLP

Project overview

We will explore the use of Socio-Technical Natural Language Processing (NLP) for classifying behavioural online harms within online forum posts (e.g. bullying; drugs & alcohol abuse; gendered harassment; self-harm), especially for young people. Our socio-technical AI will explore both zero-shot and graph-based NLP algorithms for behaviour classification, using a cyclic socio-technical methodology. This approach will facilitate incremental use of human feedback for iterative learning and re-ranking, overcoming the limited training data issue and keeping a 'human in the loop'. We follow an inclusive multi-disciplinary research approach, integrating stakeholders into our experiments from the start.

Staff

Lead researcher

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

Collaborating research institutes, centres and groups

Agents, Interaction and Complexity

We research the science and engineering of complex areas. We focus on areas including human-machine teams and human-in-the-loop interaction.
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