3D Space‐Time Visualization of Player Behaviour in Pervasive Location‐Based Games

Abstract

Location-based games not only offer new experiences for the players, but also present new challenges for researchers in terms of analyzing player behaviour. Whilst many ethnographical studies have presented useful qualitative insights into this area, there is the potential to both improve support for these studies and to provide more effective representations of the quantitative data that can often be extracted from the game itself in a manner that enables greater understanding. In this paper, we illustrate how combined spatial and temporal information can be represented using the human geographers' technique of space-time paths to provide 3D visualizations of a player's or players' movement. Our analysis of a particular location-based game shows how a richer understanding of overall game play is obtained and highlights the possibilities for using the technique for a whole range of locationbased services to provide a more complete view of complexities of journeys. Further, we discuss how these techniques can be utilized more generally by ethnographers who study the behaviour of mobile actors.

On Metrics for Location-Aware Games

“…The authors highlighted the importance of locomotion or movement "in vista space, typically a single room or sports field, or in environmental space, such as a neighborhood or city" (Montello [27] defines vista space as "space that can be visually apprehended from a single place without appreciable locomotion and environmental space as space too large and otherwise obscured to visually apprehend without considerable locomotion"), where the game takes place. Other authors define location-based games differently [28,29]. For them, these games do not necessarily require movement; they just need to take into account the user's location and/or environment.…”

“…Point-based metrics may reveal relevant game properties, such as significant locations (e.g., locations that attract players) or imbalances (e.g., locations which provide an (unfair) advantage or disadvantage). Example papers supporting this type of metrics include Coulton et al [29], where location-based metrics are employed to analyze players behavior in concrete location-based games. In particular, the distance between players as they moved around the game area, and also the mean distance from the average position, is used as a measure of "how adventurous each player was during the game".…”

“…In [39] the importance of trajectory analysis is highlighted in order to detect bots, analyzing different types of user behaviors (cooperation, flock etc), and detection of user strategies that can be indicators of game imbalance problems. Coulton et al [29] also used trajectories as a basis for analysis of players behavior (and unusual behaviors) during the game.…”

Footprints in the sky: using student track logs from a “bird's eye view” virtual field trip to enhance learning

“…Tracking data has been gathered on avatars moving in 2-D virtual space in games, virtual museums and VFTs, with various different techniques used to visualise the data (Börner & Penumarthy, 2003;Coulton et al, 2008;Oda et al, 2009;Sookhanaphibarn et al, 2011). Most pertinent for visualising our 4-D data, Chittaro and Ieronutti (2004) split the floor of a virtual museum into a grid of cells, recording the tracks of virtual visitors through the grid.…”

Spatiotemporal Analysis of Circulation Behaviors Using Path and Residing Time displaY (PARTY)

“…In addition to the aforementioned 2D visualization approaches, many visual analytics of visitor trajectories [6], [7], [8], [9] provide in 3D display by using the human geographers' technique of space-time paths. These approaches are called Space-Time-Cube that the cube consists of a representation of the geography (along the X-and Y-axis) and the time (Z-axis).…”