[2603.29651] Semantic Interaction for Narrative Map Sensemaking: An Insight-based Evaluation

Computer Science > Human-Computer Interaction arXiv:2603.29651 (cs) [Submitted on 31 Mar 2026] Title:Semantic Interaction for Narrative Map Sensemaking: An Insight-based Evaluation Authors:Brian Felipe Keith-Norambuena, Fausto German, Eric Krokos, Sarah Joseph, Chris North View a PDF of the paper titled Semantic Interaction for Narrative Map Sensemaking: An Insight-based Evaluation, by Brian Felipe Keith-Norambuena and 3 other authors View PDF HTML (experimental) Abstract:Semantic interaction (SI) enables analysts to incorporate their cognitive processes into AI models through direct manipulation of visualizations. While SI frameworks for narrative extraction have been proposed, empirical evaluations of their effectiveness remain limited. This paper presents a user study that evaluates SI for narrative map sensemaking, involving 33 participants under three conditions: a timeline baseline, a basic narrative map, and an interactive narrative map with SI capabilities. The results show that the map-based prototypes yielded more insights than the timeline baseline, with the SI-enabled condition reaching statistical significance and the basic map condition trending in the same direction. The SI-enabled condition showed the highest mean performance; differences between the map conditions were not statistically significant but showed large effect sizes (d > 0.8), suggesting that the study was underpowered to detect them. Qualitative analysis identified two distinct SI approaches-c...