This work presents a computational approach to analyze character development along the narrative timeline. The analysis characterizes changes in the protagonist’s views and behavior 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 as it is reflected in 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, a constant disposition is common, 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 for analyzing character evolution through thematic trajectories in narratives.