Evaluating Effects of Background Stories on Graph Perception

Abstract

A graph is an abstract model that represents relations among entities, for example, the interactions of characters in a novel. Background story endows entities and relations with real-world meanings and describes semantics and contexts of the abstract model, for example, the actual story that the novel presents. Considering practical experience and relevant research, human viewers who know the background story of a graph and those not knowing the story may perform differently when perceiving the same graph. However, there are currently no previous studies to adequately address this problem. This paper presents an evaluation study that investigates the effects of background stories on graph perception. We formulate three hypotheses on different aspects including visual focus areas, graph structure identification, and mental model formation, and design three controlled experiments to test our hypotheses using real-world graphs with background stories. We analyze our experimental data to compare the performance of participants who have read and not read the background stories, and obtain a set of instructive findings. First, our results show that knowing the background stories affects participants focus areas in interactive graph exploration to a certain extent. Second, it significantly affects the performance of identifying community structures but not high degree and bridge structures. Third, it has a significant impact on graph recognition under blurred visual conditions. These findings can bring new considerations to the design of storytelling visualizations and interactive graph explorations.