Understanding how players navigate through the virtual environment can offer valuable insights for game designers to build a robust and polished virtual environment. As movement is inherently spatial such an analysis can greatly benefit from utilizing supportive visualization tools. It is therefore not surprising that spatial analytics including trajectory analysis has gained popularity in the context of games user research and analytics.
In this paper, we propose a visualization tool, which is based on the concept of semantic trajectories, that is, trajectories that are augmented with semantic information. Such semantic trajectories offer a means to abstract from the exact geospatial positions while at the same time being able to visualize the movement in relation to the environment. For that purpose, our system allows to manually define areas of interest directly within the 3D editor of a game engine, which are then used to derive these semantic trajectories. To represent the data the system includes three visualizations each focusing on aggregated movement, path similarity, and individual paths. A transition diagram offers an aggregated view of the movement while individual paths can be rendered directly within the engine’s 3D view for closer inspection. A dendrogram conveys path similarity and can be used to select groups of similar paths. These three views are linked to each other such that selections in one visualization are also reflected in the others.
Through a series of interviews with six practitioners and during which they could interact with the tool, we evaluated the usefulness of the proposed approach. Comparing the insights derived from the visualization with feedback provided by the players through a post-playtesting questionnaire showed that the visualization pointed successfully to issues experienced by players. Our results indicate the potential that semantic trajectories, derived through user-guided segmentation of the game environment into important landmarks (i.e. points of interest), can offer for the analysis of movement patterns.
Contact author: Simone Kriglstein
CHI PLAY session:
Analyzing & Visualizing Player Behavior
Friday, 25 October 2019, 14:00–15:30
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