email@example.com | Research Associate
- investigating how to automatically model the interests of audiences from Twitter data using methods from machine learning and natural language programming (Barbican Arts Centre)
- developing crowdsourcing approaches to metadata generation for large audio archives (BBC)
- mining patient opinion data from Twitter (Quality Health)
I am currently working with user-generated datasets from social media and apps such as FeedFinder, to better understand the motivations and concerns of particular community groups. Another facet of the work addresses how various stakeholders can access and engage with the data insights, with a view to informing policy decisions. Before joining Open Lab I was part of the Cognitive Science research group at Queen Mary, University of London. My PhD addressed how people manage disagreements in conversation. Combining corpus analyses and experimental approaches it explored how systematically altering the presentation of someone’s stance on an issue affects the deliberative potential of a dialogue.
I enjoy working in collaboration with external organisations; previous projects include:
My research interests include: methods for measuring engagement in interaction; understanding how meaningful information can be extracted from user-generated
content; data mining approaches that account for social factors; and exploring how digital technologies can support better civic engagement.