Computational Analysis of Character Development in Holocaust Testimonies
This work provides a computational method for historical and sociological research on narratives, but it is incremental as it applies existing NLP techniques to a specific domain.
The paper tackled the problem of analyzing character development in Holocaust survivor testimonies by examining religious belief and practice trajectories, finding that most narratives show constant belief but oscillating practice patterns.
This work presents a computational approach to analyze character development along the narrative timeline. The analysis characterizes the inner and outer changes the protagonist undergoes within a narrative, and the interplay between them. We consider transcripts of Holocaust survivor testimonies as a test case, each telling the story of an individual in first-person terms. We focus on the survivor's religious trajectory, examining the evolution of their disposition toward religious belief and practice along the testimony. Clustering the resulting trajectories in the dataset, we identify common sequences in the data. Our findings highlight multiple common structures of religiosity across the narratives: in terms of belief, most present a constant disposition, while for practice, most present an oscillating structure, serving as valuable material for historical and sociological research. This work demonstrates the potential of natural language processing techniques for analyzing character evolution through thematic trajectories in narratives.