Abstract
Behavioral profiling of players in digital games is a key challenge in game analytics, representing a particular challenge in Open-World Games. These games are characterized by large virtual worlds and few restrictions on player affordances. In these games, incorporating the spatial and temporal dimensions of player behavior is necessary when profiling behavior, as these dimensions are important to the playing experience. We present analyses that apply cluster analysis and the DEDICOM decompositional model to profile the behavior of more than 5,000 players of the major commercial title Just Cause 2 integrating both spatio-temporal trails and behavioral metrics. The application of DEDICOM to profile the spatio-temporal behavior of players is demonstrated for the purpose of analysing the entire play history of Just Cause 2 players, but also for the more detailed analysis of a single mission. This showcases the applicability of spatio-temporal profiling to condense player behavior across large sample sizes, across different scales of investigation. The method presented here provides a means to build profiles of player activity in game environments with high degrees of freedom across different scales of analysis - from a small segment to the entire game.
Highlights
Behavioral profiling forms one of the core challenges of game analytics because it condenses what can be very varied, volatile and potentially high volume data about the behavior of players within the confines of a game into descriptions that highlight the patterns of player behavior [2,3,4,5, 7, 8, 10,11,12, 15, 19, 23, 25, 26, 29, 32, 33]
A technique has been presented for condensing varied, voluminous behavioral telemetry data from Open-World Games (OWGs) into distinct profiles, that describe patterns in the behavior of the players of these types of games, and which notably takes into account the spatio-temporal dimensions of the playing activity
We found that committed players were more able to harness the complete range of mechanics available to them over the course of play, as well as progress through a single mission further
Summary
Behavioral profiling forms one of the core challenges of game analytics because it condenses what can be very varied (highdimensional), volatile and potentially high volume data about the behavior of players within the confines of a game into descriptions that highlight the patterns of player behavior [2,3,4,5, 7, 8, 10,11,12, 15, 19, 23, 25, 26, 29, 32, 33]. Behavioral profiling in digital games is not a straightforward task due to the shifting requirements of a profiling exercise, common high-dimensionality in the data, volatility and the lack of clear guidelines for which types of behavioral features to incorporate into profiles [2, 3, 10, 14] These problems are notably present in games where players have wide degrees of freedom in how they want to approach and play the games, for example in some Massively Multiplayer Online Games (MMOGs) and some action-adventure games. A defining characteristic of OWG design is its facilitation of a range of player motivations and playstyles over prolonged periods of play This means that profiling of player behavior either for a section or the entire game must incorporate those same highly varied behaviors within the data and analytical techniques [2].
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