Stories shape how we understand policy issues, influencing public opinion and decision-making at times more powerfully than raw data alone, especially in complex areas like migration. But how can we systematically analyze the narratives that drive public discourse and policy?

Given the unprecedented scale of narrative construction occurring online, traditional discourse analysis methods could use some help to deal with large volumes of unstructured data. Computational Narrative Extraction (CNE) offers a way to identify and map key narratives at scale. Still, it raises critical questions: How do we measure abstract concepts like migration narratives using algorithms that rely on structure? And how can these insights support policymakers, civil society, and journalists?

This seminar explores how AI can enhance qualitative research on migration narratives, bridging computational tools with traditional discourse analysis to offer richer, more actionable insights, looking particularly at the Seeing Migration Narratives project.

Attendance is free, and all are welcome.

This seminar is hybrid.

Join us in person at Kellogg College; please arrive promptly to secure a seat.
Address: 60-62 Banbury Rd, Park Town, Oxford OX2 6PN
Google: maps.app.goo.gl/WYtGYKVbW8Xi8UMr5
To attend in person, you must register in advance: forms.office.com/e/rY5d1E4FRt

Join us online via Zoom. Click here to register: zoom.us/meeting/register/Jj4Am1xcRSSDDxO7OBlyzw