CSDE Computational Demography Working Group (CDWG): Jing Xu & Yehong Deng (05/13/26)
Posted: 4/30/2026 (Local Events)
This talk presents a novel computational analysis of history textbooks focused on the two periods, Option1 and Option 2, combining LLM-powered knowledge graph (KG) with narrative network analysis. Drawing on a refined ontology, we extract subject–predicate–object triples from a corpus of history textbooks, yielding knowledge graphs of approximately 500–800 nodes and 600–1,000 edges per tradition. We analyze structural properties including centrality, reachability, community clustering, and sentiment.
Our comparative analysis reveals systematic divergences in how historical events, entities and figures are positioned across the two traditions. Option 1 textbooks center on entities and events associated with WWII and Anglo-Irish constitutional relations, while Option 2 texts focus on civil rights, internment, and power-sharing arrangements in the Troubles era. Sentiment analysis further shows that the same entities receive markedly different evaluative framings across corpora. These structural asymmetries in narrative construction may reflect and reinforce the polarized historical identities that post-conflict education efforts seek to bridge.
Yehong Deng is a fourth-year PhD student in Sociology at the University of Washington. Her research sits at the intersection of computational social science, digital humanities, and peace education, with a focus on how historical narratives are structured and transmitted in post-conflict contexts. Her dissertation applies large language models and network analysis to study how Northern Ireland history textbooks across denominational traditions construct divergent historical narratives, drawing on knowledge graph extraction and comparative discourse analysis.
Date: 05/13/2026
Time: 10 - 11 AM
Location: Raitt 223