The Trails of Just Cause 2: Spatio-Temporal Player Profiling in Open-World Games
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The Trails of Just Cause 2: Spatio-Temporal Player Profiling in Open-World Games Myat Aung, Simon Demediuk Yuan Sun, Ye Tu, Yu Ang, Siva Nekkanti, [email protected],[email protected] Shantanu Raghav, Diego Klabjan University of York yuansun2015,YeTu2014,YuAng2015,SivaNekkanti2015: York, United Kingdom ShantanuRaghav,d-klabjan,@northwestern.edu Northwestern University Chicago, Illinois Rafet Sifa Anders Drachen [email protected] [email protected] Fraunhofer IAIS University of York Sankt Augustin, Germany York, United Kingdom ABSTRACT ACM Reference Format: Behavioral profiling of players in digital games is a key challenge in Myat Aung, Simon Demediuk, Yuan Sun, Ye Tu, Yu Ang, Siva Nekkanti, Shantanu Raghav, Diego Klabjan, Rafet Sifa, and Anders Drachen. 2018. game analytics, representing a particular challenge in Open-World The Trails of Just Cause 2: Spatio-Temporal Player Profiling in Open-World Games. These games are characterized by large virtual worlds and Games. In FDG ’19: ACM Foundations of Digital Games, August 26–30, 2019, few restrictions on player affordances. In these games, incorporat- San Luis, CA. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/ ing the spatial and temporal dimensions of player behavior is nec- 3337722.3337765 essary when profiling behavior, as these dimensions are important to the playing experience. We present analyses that apply cluster 1 INTRODUCTION analysis and the DEDICOM decompositional model to profile the Behavioral profiling forms one of the core challenges ofgame behavior of more than 5,000 players of the major commercial title analytics because it condenses what can be very varied (high- Just Cause 2 integrating both spatio-temporal trails and behavioral dimensional), volatile and potentially high volume data about the metrics. The application of DEDICOM to profile the spatio-temporal behavior of players within the confines of a game into descrip- behavior of players is demonstrated for the purpose of analysing tions that highlight the patterns of player behavior [2–5, 7, 8, 10– the entire play history of Just Cause 2 players, but also for the 12, 15, 19, 23, 25, 26, 29, 32, 33]. The purposes of profiling can be more detailed analysis of a single mission. This showcases the ap- varied, from design evaluation, progression analysis, user experi- plicability of spatio-temporal profiling to condense player behavior ence evaluation, and even purely explorative. Jointly, profiling helps across large sample sizes, across different scales of investigation. build an understanding of the users. However, behavioral profiling The method presented here provides a means to build profiles of in digital games is not a straightforward task due to the shifting re- player activity in game environments with high degrees of freedom quirements of a profiling exercise, common high-dimensionality in across different scales of analysis - from a small segment tothe the data, volatility and the lack of clear guidelines for which types entire game. of behavioral features to incorporate into profiles [2, 3, 10, 14]. These problems are notably present in games where players CCS CONCEPTS have wide degrees of freedom in how they want to approach and • Information systems → Clustering; • Applied computing play the games, for example in some Massively Multiplayer Online → Computer games. Games (MMOGs) and some action-adventure games. This is espe- cially the case for Open-World Games (OWGs) commonly referred KEYWORDS to as "Sandbox" games due to their nature. Open World Games game analytics, behavioral profiling, game development, behavior are characterized by featuring large virtual worlds that can span mining, profiling, open-world game hundreds of square kilometres of virtual real estate, with very few restrictions on the freedom of a player to go where they please; and a corresponding range of affordances, e.g. in how to accomplish ob- Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or jectives. In addition, OWGs also typically span longer game lengths, distributed for profit or commercial advantage and that copies bear this notice and with some extending into the hundreds of hours. Examples stretch the full citation on the first page. Copyrights for third-party components of this work back to Ultima Online (from 1981) which used a world design called must be honored. For all other uses, contact the Owner/Author. FDG '19, August 26–30, 2019, San Luis Obispo, CA, USA "overworld" with an Open World design. Elite (from 1984) fielded © 2019 Copyright is held by the owner/author(s). a large open section of space for players to explore. In more re- ACM ISBN 978-1-4503-7217-6/19/08. cent times, games such as The Elder Scrolls: Oblivion (2006), Skyrim https://doi.org/10.1145/3337722.3337765 (2011), Minecraft (2011), EVE Online (2003) and the Grand Theft Auto-series (1997 onwards) have all been based on OWG mechanics. FDG’19, August 26-30, 2019, San Luis Obispo, CA, USA Aung, et al. Subsequently, OWGs may have players move across their worlds 2 CONTRIBUTION several times before they are finished. Based on a dataset covering more than 5,000 players from the major The spatial and temporal dimensions of play are important in commercial title Just Cause 2, analyses are presented that apply any digital game, as they represent the dimensions that games are cluster analysis and the DEDICOM decompositional model to pro- experienced through. Work across game analytics, game AI and file player behavior in the context of open-world games. While other domains have generally incorporated one or both dimensions previous work has investigated non-spatio-temporal profiling or [14, 26, 38, 39]. Ignoring either time or space in behavioral analyses geographical trails independently [5, 12, 13, 21, 23, 37], the pre- can lead to information loss and potentially misleading results, sented technique incorporates spatio-temporal dimensions. The notably where the spatial dimension is important to the playing results provide a means for building behavioral profiles in unre- of the game [5, 9, 37]. Historically, simple visualizations of spatial stricted game environments to interpret the player experience of player behavior have been utilized, notably heatmaps. However, specific components of a game world in its entirety. heatmaps are limited in that they ignore directional and temporal information [9, 37]. 3 RELATED WORK A defining characteristic of OWG design is its facilitation ofa range of player motivations and playstyles over prolonged periods Behavioral profiling based on telemetry data from digital games is of play. However, this also means that profiling of player behavior a recent development within the larger domain of game analytics either for a section or the entire game must incorporate those same [14, 16, 20, 24], although profiling or segmentation of players in highly varied behaviors within the data and analytical techniques general has been utilized to guide game design and game AI for close [2]. This requirement is a significant justification for the necessity to two decades [4, 7, 8, 13, 15, 20, 26, 38]. Behavioral profiling in of analyzing spatial and temporal data in player research. The games is today generally driven by gameplay telemetry data or from work presented here focuses on developing profiling techniques other interactions between players and game ecosystems such as that address the requirements of OWGs specifically, integrating social media, attribution models, psychographics and demographic spatio-temporal telemetry data. information [28]. Such profiling in games is based on a variety of This game genre has not been the subject of profiling work in techniques ranging from descriptive statistics to machine learning the past. Since OWGs allow players to move freely instead of lim- utilized to address a variety of goals, including human behavior iting their trajectory to set paths, this increases the complexity of research, design evaluation, monetization, optimization, debugging making data-driven calculations as each trajectory can be theoreti- and exploration [7, 10, 13, 24, 28, 29, 33, 35]. The current work on cally unique. The profiling technique presented here significantly telemetry-based, behavioral profiling in games across academia and expands the applications of the Decomposition into Directional industry was reviewed recently by Sifa et al. [30]. Components (DEDICOM) framework adapted to games by Bauck- In parallel with the work in profiling, the visualization and eval- hage et al. [3], a spatial analysis technique that produces more uation of player behavior has been adopted across industry and detailed information than aggregate heatmaps. While Bauckhage academia. For example, Hoobler et al. [18] visualized player trails et al. [3] focused on player trails, this study integrates other dimen- and build heatmaps for Return to Castle Wolfenstein: Enemy Terri- sions of player behavior, such as characterizing player types by tory. Drachen & Schubert [9] provided a review of spatial analysis the actions performed during play. Furthermore, the DEDICOM and visualization work in games. A few examples of visualization technique has only been applied to game worlds with linear lev- work include Wallner & Krieglstein [37], which presented a visual els and shorter periods of play (a Quake III demo and an Unreal analytics system that could also handle spatial data. Mirza-Babei et Tournament 2003 level), while the application is here focused on al. [22] discussed visualization of quantitative data in detail. Nguyen the unconstrained play of OWGs across the entire playing history et al. [23] presented a visualization tool for puzzle games which of the players. This work also utilizes a large sample of real player also involved spatio-temporal operators. Miller and Crowcroft [21] telemetry of extended play duration. investigated group movement in World of Warcraft using waypoint In the solution presented here, trails are condensed to clusters modelling. With specific regard to analyzing spatio-temporal data, of checkpoints rather than raw spatio-temporal data.