Ben Medler

Ben Medler is a Ph.D. student at the Georgia Institute of Technology where he is working on his dissertation focusing on game analytics. His work revolves around the concept of Playing with Data, how developers and players can utilize game data in new, playful ways. One of his most recent projects was working with EA and Visceral Games to build a visual game analytic tool for Dead Space 2 entitled Data Cracker. A variety of other game related research projects and publications Ben has worked on include: comparing improv acting and role-playing, conflict representation in games, recommendation systems and adaptive games.

benmedler@gatech.edu

Player Dossiers: Analyzing Gameplay Data as a Reward

by Ben Medler

Abstract
Recording player gameplay data has become a prevalent feature in many games and platform systems. Players are now able to track their achievements, analyze their past gameplay behaviour and share their data with their gaming friends. A common system that gives players these abilities is known as a player dossier, a data-driven reporting tool comprised of a player’s gameplay data. Player dossiers presents a player’s past gameplay by using statistical and visualization methods while offering ways for players to connect to one another using online social networking features. This paper presents a framework for understanding how player dossiers function and fit into the process of playing games. While a common feature of player dossier systems is to merely list the rewards a player has received during play these systems also validate other gameplay motivations that may interest players besides gathering achievements. Player dossiers contextualize gameplay allowing players to analyze what they find important and share gaming information with a wider community. This turns the process of exploring past gameplay into its own reward beyond any awarded to a player in game.

Keywords: Player dossier, information visualization, game analytics, gameplay, social networks, user profiles, achievements, archiving, data mining.


Introduction

“Data is the new soil,” (McCandless, 2010) and game data is quite fertile. The ability to record and store game data has exploded in recent years (Medler, 2009) bring with it new ways of analyzing and sharing the information contained within. High scores, replays, match histories, team rankings, player ghosts, achievements, and trophies create a treasure trove of information consumed by their very creators, players. Information constantly being composed and mixed together in gratifying and useful ways, creating a situation where data is a reward unto itself.

In the midst of this creation and consumption process a new model for visualizing game data has emerged. Player dossiers are data-driven visual reports comprised of a player’s gameplay data. These reports are mediators connecting players to the vast collections of gameplay data being recorded within games from Farmville (Zynga, 2009) to Halo: Reach (Bungie LLC., 2010). A player’s in-game actions, created content and achievements are organized into dossiers representing each player’s identity, morphing over time as the player continues to play. For example, Giant Bomb (Gerstmann and Davis, 2008), a game wiki and gamer community website, creates player dossiers by visually combining achievement data from a number of gaming platforms (Blizzard Ent., 2004; Microsoft Corp., 2002; Valve Corp., 2003). Achievements are broken down by game, used to rank registered players against the average community member’s achievements and aggregated to discover the rarity of achievements within the community (Figure 1). Giant Bomb’s dossier system is essentially a visual achievement catalog for their members to peruse achievements from a different perspective.

Figure 1: Giant Bomb aggregates player data from multiple achievement systems to display player dossiers that cross genres and platforms.


With game analytics becoming a major factor for game developers (Caoili, 2010; Medler, John and Lane, 2011; Thompson, 2007), player dossiers are the converse analytic systems built for players. These systems provide new spaces for players to congregate and use visual tools to gain insights from their recorded gameplay. A game’s experience is thus extended beyond the game’s environment into these new spaces and player dossiers add their own value to the experience. Dossiers help promote competition by comparing player statistics (Ubisoft Ent., 2009), allow user-generated content to be shared (Maxis, 2009) and encourage player creativity through re-mixing game data (Evelopedia, 2010; Krush DarkGod and Urme TheLegend, 2010; Map WoW, 2006; Meyers, 2009). However, the increase reliance on related achievement systems, a common staple of player dossiers, have brought up questions regarding their effects on player behavior and game design (Hecker, 2010; Jamison, 2010). We must therefore seek to understand how player dossiers work to identify the positive and negative roles they incorporate into the gaming experience.

Figure 2: The player dossier framework identifying how gameplay is transformed into data that can be analyzed and shared.


In order to understand how player dossiers work a framework describing how these types of systems operate must be investigated. Figure 2 lays out a five part framework consisting of stages detailing both how player dossiers function and afford player actions. The first three stages explain how player dossiers are built to function by recording game data to validate player motivations and visually contextualized that data for a player’s consumption. The last two stages proclaim dossier systems afford the practices of analyzing and sharing game data to players. Each stage contributes to a feedback loop perpetrated by a player dossier system which spurs players to create more game data through continued play.

Recording Game Data

If we break apart the player dossier definition given earlier, which stated player dossiers are data-driven reports comprised of a player’s gameplay data, there are two key components: data-driven reports and a player’s gameplay data. Beginning with the former, dossiers, in general, are defined as reports describing an individual or subject. For example, athletic sports such as American baseball has recorded player and team performance statistics diligently for decades and use them in a number of ways, especially to improve a player’s or team’s performance (Medler, 2009). Player dossiers for video games are no different. A simple version of a player dossier may have a few informative points describing a player’s gameplay: length of play time, experience points gained over time, win/ loss ratios, etc. Complex player dossiers can have thousands of data points about a player. Heroes of Newerth (HoN) (S2 Games, 2010), a DoTA style strategy game (Defense of the Ancients, 2010), records over 130 data points for every match played online, in addition to the roughly 26 values aggregated over time for each separate player (kills, deaths, points earned, etc.). Those values are broken down further by a multiple of 69, which is the variety of hero units a player can choose to play in any given match (Figure 3). Consequently, HoN’s system organizes uniform dossiers for each player but the gameplay data collected for each player drives, or alters, the variable values creating divergent dossiers amongst players.

Figure 3: Heroes of Newerth player dossier system tracks hundreds of player variables for every online match.


The second component of the player dossier definition, a player’s gameplay data, comes from actually playing a game. Throughout a player’s gameplay telemetric software built into a game’s programming record player actions and other related game events (Medler, John and Lane, 2011; Mellon, 2005; Thompson, 2007). Galloway argues that player actions can be broken down into diegetic and nondiegetic actions (Galloway, 2006) [1]. Diegetic actions are those related to the “the game’s total world narrative action” (Galloway, 2006, p.7). Running, speaking with game characters and solving a puzzle while in the game world are examples of diegetic actions. Nondiegetic actions are “gamic elements that are inside the total gamic apparatus yet outside the portion of the apparatus that constitutes a pretend world of character and story” (Galloway, 2006, p.7) like pressing the start button or using a heads-up display in a game. Both diegetic and nondiegetic actions happen in the “total world” or “total gamic apparatus” which refers to space of time when gameplay actions occur and can be recorded by a telemetric system.

However, most player dossier systems are extra-diegetic. They exist outside of what Galloway describes as the “total gamic apparatus.” As an extra-diegetic feature, player dossiers are often included amid separate online systems or services offered by a game’s developer. Some games do display player dossiers in-game separate from the gameplay experience (Blizzard Ent., 2010a; Electronic Arts Inc., 2010; Nintendo EAD, 2007) but dossier systems are largely still found online as part of a website related to a game (Blizzard Ent., 2010b; Blue Byte Software, 2010; Bungie LLC, 2004; S2 Games, 2010). Additionally, developers create APIs (Microsoft Corp., 2002; Blizzard Ent., 2010b; Valve Corp., 2003) that allow third-party services to connect with databases filled with player gameplay data. This has spawned a new series of third-party player dossier services (Gerstmann and Davis, 2008; Radoff, 2006) that combine multiple games from various platforms, creating systems that would be impossible for any single developer to offer using their gameplay data alone. Giant Bomb (Gerstmann and Davis, 2008), as referenced in the introduction, is an example that combines player achievement data from Microsoft’s (Microsoft Corp., 2002), Steam’s (Valve Corp., 2003) and World of Warcraft’s (Blizzard Ent., 2004) achievement systems. Thus, player dossiers are defined reports driven by recorded gameplay data, displaying the achievements earned and actions performed by players but exist outside of gameplay.

As an auxiliary consequence to displaying gameplay data, player dossier systems also validate player motivations for playing games. The motivations that compel players to play, such as the feeling of mastery or the urge to explore, are confirmed by various dossier variables. Players motivated to master the game are validated through having their username sit atop a leaderboard while players motivated by exploration are shown game maps of their in-game expeditions. Understanding how player dossiers work must include an analysis of the types of motivations that compel players and how those motives are epitomized.

Validating Motives

Players are motivated to play games for different reasons as is often argued by researchers studying player types (Bartle, 2003; Lazzaro, 2009; Yee, 2007). Yee, for instance, breaks down player motivation into three sub-categories: Achievement, Social and Immersion (Yee, 2007). Players with achievement motivations focus on advancement within the game, optimizing their gameplay using a game’s mechanics and competing with other players. Social motivations involve socializing, forming relationships and working with a team. Finally, the immersion category contains motivations for discovering hidden gameplay elements, roleplaying, game customization and escaping from the real world. Other motivation frameworks break down motives into similar categories. Lazzaro breaks down motivation into four emotional categories that players feel when having fun playing games: hard fun (e.g. competition and achievement), easy fun (roleplay and discovery), serious fun (escape and advancement), and people fun (socializing and customization) (Lazzaro, 2009). Player motivation seems to be multifaceted, given the research surrounding player types, stretching the concept of what is important and qualifies as a “reward” for players.

Regardless of which motivations drive a player’s gameplay we can say that those motivations affect their gameplay behaviour. Players who are motivated by achievement will strive to earn more trophies and similarly a player motivated to socialize will seek out new in-game relationships. As a result, player dossiers are a means of validating those motives because they provide a representation of a player’s gameplay. Achievers will find that player dossier systems display awards earned within a game, such as Giant Bomb’s achievement system. Other motivations like socializing are often covered within player dossier system because they allow players to monitor their friend’s data (Bungie LLC., 2004), comment on replays (S2 Games, 2010), or share their data on other social networks (Blizzard Ent. 2010c). However, one should question if all gameplay motivations are represented in player dossier systems or only a certain subset.

With the rise of achievements as a standard practice for rewarding players who accomplish certain goals (Medler, 2009) game companies have been accused of focusing too heavily on achievement rewards and the motivations behind obtaining them (Hecker, 2010; Jamison, 2010). Motivations are often associated with a reward system, a player is motivated to work towards goals or achievements that interest them. How those motivations relate to the activity, that is, playing a game, is often described as the difference between extrinsic and intrinsic motivations (Dweck, and Leggett, 1988; Elliot, 2005). Extrinsic motivators are detached from the activity being performed; most tangible rewards are regarded as extrinsic rewards. A trophy, an extrinsic reward, given to a professional gamer for winning a game tournament is an extrinsic motivator because the trophy itself has nothing to do with the actual game played. Conversely, the motivating feelings the professional gamer experiences while playing in a tournament, those of accomplishment and of attaining a mastery of the game, are intrinsic motivations since those feelings directly relate to the act of playing the game.

If game companies focus too heavily on achievements then they are promoting extrinsic rewards rather than fostering other intrinsic motivations for playing games (Hecker, 2010). Some psychology researchers have argued that extrinsic motivators “undermine” intrinsic motivation by forcing individuals to expect a reward for an activity (Greene and Lepper, 1974) or that extrinsic rewards take away from an activities inherent intrinsic properties (Weiner, 1995). However, these arguments have been called into question as using circular logic (Reiss, 2005). For example, if a player is given an extrinsic reward for completing a level in a game and stops playing, it is argued that the player’s intrinsic motivation has been undermined and decreased. Whereas if they continue to play the game it is argued that the player is now continuously expecting a reward and is forever extrinsically motivated. In either case it is impossible for intrinsic motivation to re-enter as a reason for the player’s behaviour, creating a situation where the undermining factor is always reinforced (Reiss, 2009). Additionally, other research reveals there are certain types of people that benefit from extrinsic motivators like rewards (Elliot and Church, 1997; Lee, Sheldon and Turban, 2003). One argument finds achievements, “goals and outcomes, as well as their evaluations, are to a large extent a matter of social determination” (Hareli and Weiner, 2002, p.183). In social settings extrinsic rewards are seen by some as displaying competence in an area to others (Elliot and Church, 1997) or present challenges to compete with other members of a social group (Lee, Sheldon and Turban, 2003). There seems to be no clear cut argument for or against presenting extrinsic rewards as positive motivators for individuals, especially players.

Perhaps a different way to look at motivation, instead of reducing them to extrinsic and intrinsic categories, is to take a multifaceted approach similar to the methods that player type researchers take when describing player motivations. Riess argues that “motivation is fundamentally multifaceted and cannot be reduced to just two sources,” stating that multiple categories of motives actually drive individuals to perform certain tasks (Riess, 2005, p.7). These motives include: power, curiosity, independence, status, social contact, vengeance, honor, idealism, physical exercise, romance, family, order, eating, acceptance, tranquility, saving. While these motives do not represent an exhaustive list they match quite well the gameplay motives other researchers have found:

  • Power and status fit with Yee’s competition category and Lazzaro’s hard fun. Player dossier systems represent those motivations through displaying achievement awards and ranking players based on measurements such as score or speed.
  • Curiosity and saving are similar to discovery, advancement and easy fun. Red Dead Redeption’s (Rockstar San Diego and Rockstar North, 2010) player dossier system, as examined in the next section, shows players the areas they have explored in the game while other systems mark when player’s have found hidden objects or locations.
  • Social contact and vengeance relate to competition, socializing and people fun. Most player dossier systems have the ability for players to track friends but can also be used to track rival players or guilds.
  • Tranquility matches the escapism and serious fun motivations. While these motivations are harder to validate, player dossiers are systems that extend a game’s experience beyond the game itself and can provide the same type of escapism that games offer.

Other motivations like eating would be hard to represent, being tangible, but motivations like physical exercise can be represented through player dossier systems built into Wii Fit (Nintendo EAD, 2007) or EA Sports Active (EA Vancouver, 2009). The motive of honor is represented in Starcraft 2 (Blizzard Ent., 2010a), a real time strategy game, by accumulating the number of times the player disconnects in an online match [2]. Player dossiers certainly do not validate every motivation that a player may feel while playing a game but these systems certainly represent motivations beyond those argued to be only extrinsic.

In order for a player dossier system to validate motivations using gameplay data it must present that data to players in a coherent and meaningful way. Throwing mounds of gameplay data at players is not helpful unless it is contextualized--ideally in such a way that relates to the motivations for playing a game.

Contextualizing Gameplay

A common motto in information visualization literature is “data without context is meaningless,” data must have some point of reference to be properly understood or analyzed (Few, 2009; Spence, 2001; Tufte, 1983). Visualization and analytic systems must have the “ability to clearly and accurately represent information” and give users the “ability to interact with it to figure out what the information means” (Few, 2009, p.55). Similarly, player dossiers should present gameplay data in context to gameplay and provide an interactive system for players to gain insight or enjoyment from analyzing the data.

Three player dossier systems are examined to show how they place gameplay data into context given their respective game. This first includes Bungie’s online portal for Halo statistics (Bungie LLC, 2004), Halo being a franchise of popular first-person shooter games, which covers player achievements, winning percentages, and detailed information about the matches played by teams of players. The second dossier system is the Armory (Blizzard Ent.,2010b) built for World of Warcraft (Blizzard Ent., 2004), a fantasy massively multiplayer online (MMO) roleplaying game, and focuses on a player’s avatar configurations. Finally, Red Dead Redemption, an open-world action adventure game set in the wild west, has a player dossier system built into Rockstar’s Social Club online community (Rockstar Games, 2008) which keeps track of how players explore the game environment and progressed through the game’s storyline.

Bungie.net - Combat is the most important aspect of any Halo game whether it is the combat from the single player campaign in Halo 3: ODST (Bungie LLC., 2009) or the multiplayer matches of Halo:Reach [3]. Bungie’s player dossier system contextualizing player gameplay data around combat and breaks player data down into different areas associated with each game’s combat modes. When players log into Bungie.net they are presented with an overview report of their past combat achievements (Figure 4) and then allowed to move on to more detailed information. This method of presenting overview data first is a mantra within the information visualization community, “overview first, zoom and filter, then details-on-demand,” (Shneiderman, 1996) and is used in most player dossier systems. Once a player dives into the Halo system he or she can view further combat data related to their: progression through each game’s campaign levels, past multiplayer matches and experience rankings over time. Combat data from campaign and multiplayer matches includes recording the players kill count, which weapons they used, if any awards were gained and time of completion. This data is organized using multiple visual formats, e.g. data tables, heat maps and sun burst graphs. These visualizations, along with leaderboards and achievement tracking, quantify how combat effect players are in the game.

Figure 4: Most player dossier systems display different levels of detailed player data based on where the player is at in the system.


World of Warcraft Armory - The main feature of the World of Warcraft Armory player dossier system focuses on exhibiting each player’s avatar from the game. The Armory uses similar artwork and functionality from World of Warcraft (WoW) for displaying avatars and their related information (Figure 5). The avatar’s appearance, item descriptions and combat values are all available to a player through their Armory profile. Other data points about a player’s avatar are also displayed including: talents, reputation, achievements, Player verses Player (PvP) standings and guild information. Having a similar setup found in WoW makes it easier for players to automatically understand how to use the Armory and begin taking advantage of data provided. Players can easily jump from their own avatar to their friend’s avatar page before heading over and assessing a rival guild’s roster. Since WoW is an MMO the Armory’s features are indicative of how players focus on their personal game personas and the connection they create between other players.

Figure 5: The World of Warcraft Armory draws heavily from the game’s artwork and interaction to provide an online experience very similar to one found in the game.


Red Dead Redemption - Open world games allow players to explore wide, virtual landscapes and get players involved in storylines spanning different areas. That’s why Red Dead Redemption’s player dossier system focuses on exploration, collecting and story related data. First, the system displays a map of where players have been which is very similar to the one players use in the game (Figure 6). There are many collectables or sets of events that can occur in the game (finding bandit hideouts, finishing story events, collecting bounties, completing mini-games) and all of them are laid out in the system clearly delineating the ones left to complete or collect. Additionally, there are lists of achievements players have earned and statistics that may not be important to gameplay but are certainly interesting events as the player traverses the environment (e.g. hogtieing criminals or the number of horses a player has owned). All of this data helps players absorb the vastness of an open-world game, monitor what they have experienced thus far and plan where to go next.

Figure 6: The map players use while playing Red Dead Redemption is duplicated in the Rockstar’s online player dossier system for the game.


Each of these player dossier systems captures player data and adds context to match the main focus of each game. Combat and strategy focused games like those in the Halo franchise present data that relates to how a player performs against AI or player opponents. Roleplaying and massively multiplayer games will tend to present data related to a player’s avatar and link their data with their guild or friends. Player dossier systems for adventure and open-world games follow the players progression through the story and presents data related to the player’s exploration of the game. Still other examples of player dossier systems combine data from multiple games, such as Giant Bomb’s achievement dossier (Gerstmann and Davis, 2008), but each attempts to present gameplay data in such a way as to make it easier for players to gain insights from analyzing their data.

Analyzing Dossiers

The way that player dossiers validate and contextualize gameplay data is very similar to how online user profiles function. Both types of systems allow users the ability to provide personalized data and construct meaningful information about their identity, which is consumed by other users. However, the major difference between player dossiers and user profile systems is that players can gain insights from analyzing their own gameplay information, which is automatically generated instead of being intricately constructed.

A lot of emphasis is placed on user profiles in online spaces. Whether in games, social networks, forums or blogs, a profile is a product of self-expression that presents a user’s identity to an online community. For example, on a social network a user may include their tastes in entertainment (Liu, 2007), a list of hobbies or other personal demographic information that they wish other users on the network to know (Ellison, Steinfield and Lampe, 2007). For game related websites like Newgrounds (Fulp, 1995), an online portal for Flash content, a user may list their favorite games that appear on the site or their own work built using the Flash platform. Users deliberately add this information and are further permitted to make alterations to their self-described data as they see fit (Walther, 2007). While allowing such freedom can endorse the behavior to “enhance” ones identity, essentially lying, many users are relatively accurate with the information they provide (Toma, 2010; Toma, Hancock and Ellison, 2008). However, this means that information cannot be entirely trusted on user profiles.

Player dossiers work differently. While player gameplay data is certainly collected from a player’s personal actions, players do not have the level of intentional control over the dossier’s content as they do with profiles. A player has control over their motives to pursue an objective and may choose to play a game in a specific way, but those decisions are tangential to how a dossier represents the results of those motivations. Dossiers often have a specific purpose and represent targeted information given back to the player after gameplay concludes. A Red Dead Redemption player cannot change how many locations they have visited on their dossier unless they explore new areas within the game. Winning or losing a game in Halo 3 (Bungie LLC., 2007) is important while playing and the outcome of a match will forever be recorded in a player’s dossier report due to that importance, without the ability for players to alter the results. If “our reputations depends upon how other people judge and evaluate us” (Solove, 2007, p.33) then players are deprived of the ability to guide the narrative of their online reputation within player dossier systems in comparison to user profiles. Enhancing one’s own identity becomes much harder.

However, at the same time a player becomes a voyeur of their own historical gameplay. They can monitor and analyze their past behavior instead of focusing on creating their identity, as they are forced to do when creating a profile. Games are excellent tools for learning (Gee, 2007), and player dossiers give users the ability to learn from their past experiences. For example, Starcraft 2 (SC2) replays, which are linked to a player’s SC2 dossier, record the exact times and order of every building and unit created in a multiplayer match. Players can use that information to see how their strategy unfolded during the match and where they can improve. Dossiers also help players monitor their progress through a game by keeping aggregated totals of variables like experience, achievements earned or missions completed. Wii Fit’s dossier shows a player’s fitness progression over time while services like Giant Bomb keep track of how many achievements players have left to gain in each of their games.

Player dossiers certainly offer the unique ability to analyze one’s past compared to user profiles, but these two systems can often be found intermixed. Heroes of Newerth’s dossier system allows players to leave comments about matches, giving players a chance to direct the conversation surrounding their past gameplay. Players using Rockstar’s Social Club can upload videos that they made within games like Grand Theft Auto 4 (Rockstar Toronto, 2008) or Red Dead Redemption, giving the player more power over what information is being presented to outside audiences. Hence, the final piece of the player dossier framework is how players move from analyzing and consuming their own data towards sharing knowledge within a game’s community, thus moving gameplay data away from being merely personal capital, and only useful for the individual, to social capital.

Creating Social Capital

Player dossier systems offer the means for sharing gameplay data socially between players in addition to players reflecting on their own data. Ad-hoc social networks are often featured in player dossier systems, where many systems are open for public viewing and offer friend connections. Being both public and interconnected, player dossiers offer similar benefits that social networks provide (Ellison, Steinfield and Lampe, 2007) and can be argued as an aid for players to create social capital in the system.

Social capital can be defined as “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance and recognition” (Bourdieu, 1983, p.248). Other definitions have been used (Adler and Kwon, 2002) but in general an individual’s social capital is equivalent to the resources that their social connections can mobilize in terms of “economic, cultural or symbolic” capital (Bourdieu, 1983, p.249). Social capital can be beneficial to individuals within social groups as a means of sharing information and providing emotional support (Paxton, 1999). Therefore, if player dossier systems can provide some form of social capital to players then dossier reports may be rewarding for players from a social stand-point.

One way to show how player dossiers can provide social capital to players is to use Putnam’s dimensions of bonding and bridging social capital. Bonding social capital “tends to reinforce exclusive identities and homogeneous groups” and can provide “social and psychological support” for members of a group (Putnam, 2000, p.22). Taylor’s work revolving around power gamers show how those players are “highly networked” within their game’s community (Taylor, 2006) and produce bonding social capital. They participate regularly on game strategy forums, maintain online and offline relationships related to their game and form the ranks of many in-game guilds, all of which provide them social support and reinforce their identity as power gamers. Bridging social capital is instead “outward looking and encompass people across diverse social cleavages” and “are better for linkage to external assets and for information diffusion” (Putnam, 2000, p.22). Media technology is very good at providing what Haythornthwaite calls latent ties, the technical ability to create bridging social capital (Haythornthwaite, 2005), which are also called “weak ties” (Granovetter, 1982). For instance, online social networks provide users with the technical abilities to forge new social relationships--and therefore create weak ties among users--by providing features for communicating and allowing personal information to be shared (Ellison, Steinfield and Lampe, 2007). Users can gauge another user’s personal information quickly or gain new perspectives from one another within a social network without necessarily having relationships that are emotionally supportive (Ellison, Steinfield and Lampe, 2007; Granovetter, 1982).

Player dossier systems are generally open to a game’s player community making it easy to share information and can be argued as having the same power as social networks to create weak ties among players. GamerDNA (Radoff, 2006), a social network for game players, keep track of each of their registered player’s gameplay activity by monitoring networks like Xbox Live (Microsoft Corp., 2002) and the PlayStation Network (Sony Computer Ent., 2006) to provide players with knowledge about each other’s gaming habits. Player dossiers on GamerDNA include breaking down a player’s games by genre and platform, streaming events such as when a player first played a game or earned achievements, and other gamer traits which are created when players answer surveys regarding their gameplay behaviour (Figure 7). While GamerDNA does not access specific gameplay data compared with player dossier systems found in Starcraft 2 or Red Dead Redemption, the system allows users to quickly find relevant information through the weak ties it creates between players with similar gaming habits and traits. For instance, players that have recently started a mutual game may have a better chance of interacting by using GamerDNA, which have features that connect users playing the same game, than the players using the game’s internal communication systems.

Figure 7: GamerDNA asks players to take a number of surveys which they then visualize as a set of player gaming traits.


Another form of knowledge transfer that can happen within player dossiers systems is when players find gameplay examples that are above their skill level. Heroes of Newerth’s players can rank which replays they enjoy, which both directs players to popular replay files they may enjoy and links players to the specific players that participated in those replays. These weak ties that exist between players make it easier for players who wish to become better at a game to find examples of exquisite gameplay (Medler, 2009) whereas in the past this information was often locked away in power gamer groups (Taylor, 2006). However, having a large amount of weak ties does not mean that users are immediately powerful (Cha et al., 2010). The quality of the content offered still plays a major roll, which means that players such as power gamers can still provide better quality content. However, player dossier systems make it easier for other players to tap into that extensive community knowledge pushing players to return to their games armed with new gameplay strategies; and the player dossier cycle begins once more.

Discussion and Conclusion

From gameplay to gameplay, the player dossier framework (Figure 2) brings full circle the ability to use captured gameplay as a means to entice players to continue playing. All player dossiers record diegetic/ non-diegetic gameplay data creating a personal account of a player’s game experience. The motivations behind a player’s gameplay are then validated in a player dossier system and bring more value to the player than just displaying “extrinsic” rewards. Validated values are then contextualized to make it easier for players to understand their data, and each player dossier system focuses on different aspects of the game it supports. Players then have the ability to analyze their gameplay data; player dossiers not only award players with a trophy room but a chance to learn from their behavior. Last, players can gain social capital by using player dossier systems creating weak ties between other players and allow for information transfer that would otherwise be locked within obscure gaming sub-groups. Once players begin to analyze their own behavior and the behavior of other players this ultimately leads to players continuing the cycle, creating more gameplay data. This is not to say that player dossiers are the only cause for continued gameplay but that player dossiers are “living” systems, providing a persistent glimpse into a player’s motivations and their accomplishments and rewarding players for exploring and sharing gameplay that retains its value as long as players continue to play.

While the arguments for the framework presented thus far have featured the benefits of player dossiers, there are limitations and issues to these systems that are necessary to cover. One major limitation is the lack of player dossier research. Tangential research exists that has briefly mentioned similar systems compared to the player dossier examples provided in this article. Such research, for example: game studies research into players cheating using game databases similar to the WoW Armory (Consalvo, 2007); into virtual economies and how statistic tracking plays an economic role (Castronova, 2006); into power gamers using performance monitoring software (Taylor, 2006), and game metrics being collected to discover behavior habits in virtual worlds (Williams, Yee and Caplan, 2008) have only slightly referred to player dossiers.

Additionally, player dossier research does not have to focus on systems supported by game developers. There are examples of player groups tracking their own statistics or using game data to build useful systems for other players [4]. Even developer-produced dossier systems have mimicked other player-created systems. For example, the WoW Armory was built after other player-run systems such as thottbot.com and allakhazam.com had been in service for many years. There are certainly many avenues for future player-dossier research to pursue.

Another limitation is that the current analysis abilities offered in player dossier systems are quite few compared to the analytic methods used for data mining. Player dossier systems typically use aggregated totals for displaying gameplay data, but players do not have the ability to find trends or analyze data beyond what a system provides. Data mining has proved useful for AI research such as building game narratives (Sharma, et al. 2010) or smarter AI opponents (van Hoorn, et al. 2009; Weber and Mateas, 2009), but these systems are not provided to the players themselves. This may be due to the fact that data mining as a practice, and related fields like machine learning, is difficult (Patel, 2010). However, there are examples of fighting games that have primitive data mining features that record player actions to create AI agents and interact with the player directly. Virtua Fighter 4 (Sega-Am2, 2002) and recent games in the Tekken series give players the option to create their own “player ghosts” (Medler, 2009), AI controlled opponents that learn from a player’s gameplay data. Virtua Fighter 4 players, for instance, can train their ghosts by fighting against them or judging their fighting style in replays. Other player dossier systems, such as the one built into Starcraft 2, already link players to their replays as well. Given the research into using data mining for producing smarter Starcraft opponents (Weber and Meteas, 2009) build data mining features into the Starcraft 2’s player dossier system is not out of the question.

Finally, there are ethical issues that need to be addressed when using and developing player dossier systems. Near the end of 2009, Blizzard Entertainment, the makers of World of Warcraft, helped local United States police track down a criminal suspect who played WoW (Munsey, 2009). The suspect had a warrant out for his arrest but had left the country making it difficult for the police to locate him. That is until the police found out the suspect continued to play WoW and requested Blizzard’s help in finding the suspect. Blizzard responded by giving the police a number of data points about the suspect, including his IP address and gameplay habits. The IP address alone was enough to roughly pinpoint the location of the suspect, who was in Canada, and lead to the apprehension of the suspect.

The actions taken by Blizzard raise issues concerning the purpose of collecting data and game developers must pause to consider these ethical concerns. Stored data lingers for much longer than users remember and can come back to haunt them (Mayer-Schönberger, 2009; Solove, 2007). There are examples of employees getting fired for comments placed online, people being deported to other countries because of mistaken identity, and online reputation systems being cheated to hurt businesses or users. Developers have to remember that collected player data represents an “out-of-context” piece of someone’s life (Mayer-Schönberger, 2009). While player dossiers do provide the means of promoting repeat gameplay and building a player community online it is also important to decide how the privacy and anonymity of player data will be handled.

Player dossiers are always evolving [5] and are becoming a necessary feature for games that continue to integrate online capabilities. As a result, developers must be aware of the current functional limitations and ethical issues that come with building telemetric based systems. Despite these facts, player dossiers provide important functions by creating spaces for player communities, visually displaying player achievements in an online forum and allow gameplay knowledge to flow between players more freely. It is up to both players and game developers to find common ground through the development of these systems to find proper methods for using gameplay data to extend the game experience.

End Notes

[1] Galloway also specifies another dimension of gameplay actions which states whether the "operator" (i.e. player) or "mechanic" (i.e. game) performs the action. This paper is assuming that all data is related to player actions.

[2] Disconnecting from a multiplayer game refers to a player disconnecting their network connection during an active match. In the past, disconnecting from a game meant the game ended in a draw and was therefore a practice used most often when a player realized they could not win the game. Many games now attempt to disclose which players disconnect the most in order to discourage the practice.

[3] Bungie.net records data from Halo 2, Halo 3, Halo 3: ODST and Halo: Reach.

[4] One example is a group of Darkfall players that record which guilds own territory within the game world and produce updated Darkfall maps (Krush DarkGod and Urme TheLegend, 2010).

[5] Blizzard Ent. completely overhauled the design of the WoW Armory, in anticipation for the game’s new expansion, while this article was being written.

References

Adler, P., & Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 17 - 40.

Bartle, R. (2004). Designing Virtual Worlds. Berkeley, CA: New Riders.

Blizzard Ent. (2004). World of Warcraft. [PC], USA: Blizzard Ent.

Blizzard Ent. (2010a). Starcraft 2: Wings of Liberty. [PC], USA: Blizzard Ent.

Blizzard Ent. (2010b). World of Warcraft Armory. Retrieved January 10, 2010 from us.battle.net/wow/en/.

Blizzard Ent. (2010c). World of Warcraft Armory Facebook Application. Retrieved January 10, 2010 from apps.facebook.com/wow-armory.

Blue Byte Software. (2010). The Settlers 7: Paths to a Kingdom. [PC], France: Ubisoft.

Bourdieu, P. (1983). The Forms of Capital. J. G. Richardson (Eds.), Handbook of Theory and Research for the Sociaology of Education. New York: Greenwood Press.

Bungie LLC. (2004). Bungie.net. Retrieved July 24, 2010 from www.bungie.net.

Bungie LLC. (2004). Halo 2. [Xbox], Microsoft Game Studio.

Bungie LLC. (2007). Halo 3. [Xbox 360], Microsoft Game Studio.

Bungie LLC. (2009). Halo 3: ODST. [Xbox 360], Microsoft Game Studio.

Bungie LLC. (2010). Halo: Reach. [Xbox 360], Microsoft Game Studio.

Caoili, E. (2010). Zynga Chooses Tableau For Data Visualization, Analysis. Gamasutra. Retrieved August, 20, 2010 from www.gamasutra.com/view/news/28408/.

Castronova, E. (2006). Synthetic Worlds: The business and culture of online games. University of Chicago Press.

Cha, M., Haddadi, H., Benevenuto, F., and Gummadi, K. P. (2010). Measuring User Influence in Twitter: The Million Follower Fallacy. In Proceedings of the 4th International AAAI Conference on Weblogs and Social Media (ICWSM).

Consalvo, M. (2007). Cheating: Gaining Advantage in Videogames. MIT Press.

Defense of the Ancients. (2010). In Wikipedia, The Free Encyclopedia. Retrieved August 23, 2010 from en.wikipedia.org/w/index.php?title=Defense_of_the_Ancients&oldid=381923500.

Dweck, C. S., and Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273.

EA Vancouver. (2009). EA Sports Active. [Nintendo Wii], USA: EA Sports.

Electronic Arts Inc. (2010). Autolog. Retrieved December 1, 2010 from hotpursuit.needforspeed.com/game-info/autolog.

Elliot, A. J. (2005). A conceptual history of the achievement goal construct. In A. Elliot & C. Dweck (Eds.), Handbook of competence and motivation, (pp. 52 - 72). New York: Guilford Press.

Elliot, E. S., & Church, M. A. (1997). A hierarchal model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72, 218-232.

Ellison, N. B., Steinfield, C. and Lampe, C. (2007). The Benefits of Facebook ‘‘Friends:’’ Social Capital and College Students’ Use of Online Social Network Sites. Journal of Computer-Mediated Communication, 12, 1143 - 1168.

Evelopedia. (2010). Territorial maps. Retrieved December 5, 2010 from wiki.eveonline.com/en/wiki/Territorial_maps.

Few, S. (2009). Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press.

Fulp, T. (1995). Newgrounds. Retrieved August 21, 2010 from www.newgrounds.com.

Galloway, A. R. (2006). Gaming : Essays On Algorithmic Culture (Electronic Mediations). Univ Of Minnesota Press.

Gee, J. (2007). Good Video Games + Good Learning: Collected Essays on Video Games, Language, and Learning. New York: Peter Lang.

Gerstmann, J. and Davis, R. (2008). Giant Bomb. Retrieved July 24, 2010 from www.giantbomb.com.

Granovetter, M. S. (1982). The Strength of Weak Ties: A network theory revisited. In P. V. Mardsen & N. Lin (Eds.), Social Structure and Network Analysis (pp. 105 - 130). Thousand Oaks, CA: Sage Publications.

Greene, D., & Lepper, M. R. (1974). How to turn play into work. Psychology Today, 8, 49-54.

Hareli, S. and Weiner, B. (2002). Social Emotions and Personality Inferences: A Scaffold for a New Direction in the Study of Achievement Motivation. Educational Psychologist, 37(3), 183 - 193.

Haythornthwaite, C. (2005). Social networks and Internet connectivity effects. Information, Communication, and Society, 8(2), 125 - 147.

Hecker, C. (2010). Achievements Considered Harmful?. Game Developers Conference 2010. San Francisco.

Jamison, P. (2010). FarmVillains. SF Weekly (2010). Retrieved September 10, 2010 from www.sfweekly.com/2010-09-08/news/farmvillains/.

Krush DarkGod and Urme TheLegend. (2010). Darkfall Political Map - Server US1. Retrieved December 5, 2010 from darkfallinfo.com/pmap/?mapserver=us1.

Lazzaro, N. (2009). Understand Emotions. In C. Bateman (Eds.), Beyond Game Design (pp.3-48). Boston: Course Technology.

Lee, F. K., Sheldon, K. M., & Turban, D. B. (2003). Personality and the goal striving process: The influence of achievement goal patterns, goal level, and mental focus on performance and enjoyment. Journal of Applied Psychology, 88, 256-265.

Lewis, C. and Wardrip-Fruin, N. (2010). Mining game statistics from web services: a World of Warcraft armory case study. In Proceedings of Foundation of Digital Games Conference, 100-107. Monterey, Ca.

Liu, H. (2007). Social network profiles as taste performances. Journal of Computer-Mediated Communication, 13, 1. Retrieved July 24, 2010 from jcmc.indiana.edu/vol13/issue1/liu.html.

Macklin C., Wargaski, J., Edwards, M. and Li Kan, Y. (2009). DATAPLAY: Mapping Game Mechanics to Traditional Data Visualization. In Proceedings of DiGRA 2009. London, UK.

Map WoW. (2006). Retrieved July 24, 2010 from www.mapwow.com.

Maxis. (2009). Spore API. Retrieved July 24, 2010 from www.spore.com/comm/developer.

Mayer-Schönberger, V. (2009). Delete: The Virtue of Forgetting in the Digital Age. Princeton University Press.

McCandless, D. (2010). The Beauty of Data Visualization. TEDGlobal 2010. Retrieved August 25, 2010 from www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html.

Medler, B. (2009). Generations of Game Analytics, Achievements and High Scores. Eludamos - Journal for Computer Game Culture, 3(2), 177-194.

Medler, B., John, M. and Lane, J. (2011). Data Cracker: Developing a Visual Game Analytic Tool for Analyzing Online Gameplay. In Proceedings of CHI 2011. Vancouver, BC Canada. (in press)

Medler, B. and Magerko, B. (2011). Analytics of Play: Using Information Visualization and Gameplay Practices for Visualizing Video Game Data. Parsons Journal for Information Mapping, 3(1).

Mellon, L. (2005). Metrics Collection and Analysis. In T. Alexander (Eds.), Massive Multiplayer Game Development 2 (pp. 243-255). Hingham, Ma.: Charles River Media.

Meyers, A. (2009). Spore Skeletons. Retrieved on July 20, 2010 from www.universaloscillation.com/sporeskeletons/.

Microsoft Corp. (2002). Xbox Live.

Munsey, P. (2009). Long arm of law reaches into World of Warcraft. Kokomo Perspective. Retrieved on January 1, 2010, from kokomoperspective.com/news/local_news/article_15a0a546-f574-11de-ab22-001cc4c03286.html.

Nintendo EAD. (2007). Wii Fit. [Nintendo Wii], Japan: Nintendo.

Patel, K. (2010). Lowering the Barrier to Applying Machine Learning. In Proceedings of CHI 2010, 2907-2910. Atlanta, Ga.

Paxton, P. (1999). Is social capital declining in the United States? A multiple indicator assessment. American Journal of Sociology, 105(1), 88 - 127.

Putnam, R. D. (2000). Bowling Alone. New York: Simon & Schuster.

Radoff, J. (2006). GamerDNA. Retrieved August 21, 2010 from www.gamerdna.com.

Reiss, S. (2005). Extrinsic and intrinsic motivation at 30: Unresolved scientific issues. The Behavior Analyst. 28(1), 1 - 14.

Reiss, S. (2004). Multifaceted Nature of Intrinsic Motivation: The Theory of 16 Basic Desires. Review of General Psychology. Vol. 8, No. 3, 179 - 193.

Riess, S. (2009). The Myths of Intrinsic-Extrinsic Motivations. Retrieved on August 7, 2010 from www.psychologytoday.com/blog/who-we-are/200911/the-myths-intrinsic-extrinsic-motivation.

Rockstar Games. (2008). Rockstar Games Social Club. Retrieved 24 July 2010. Website: socialclub.rockstargames.com.

Rockstar San Diego and Rockstar North. (2010). Red Dead Redemption. [Xbox 360], USA: Rockstar Games.

Rockstar Toronto. (2008). Grand Theft Auto IV. [PC], USA: Rockstar Games and Take-Two Interactive.

S2 Games. (2010). Heroes of Newerth. [PC], USA: S2 Games.

Sega-AM2. (2002). Virtua Fighter 4: Evolution. [PS2], Sega.

Sharma, M., Ontañón, S., Mehta, M. and Ram, A. (2010). Drama Management and Player Modeling for Interactive Fiction Games. Computational Intelligence Journal, 26(2), 183-211.

Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy of information visualizations. In Proceedings of IEEE Visual Languages 1996, 336 - 343.

Solove, D. J. (2007). The Future of Reputation. New Haven: Yale University Press.

Sony Computer Ent. (2006). PlayStation Network.

Spence, R. (2001). Information Visualization. ACM Press.

Taylor, T. L. (2006). Play Between Worlds. Cambridge, MA: MIT Press.

Thompson, C. (2007). Halo 3: How Microsoft Labs Invented a New Science of Play. Wired, 15(9). Retrieved on January 10, 2011 from www.wired.com/gaming/virtualworlds/magazine/15-09/ff_halo.

Toma, C. L. (2010). Affirming the Self through Online Profiles: Beneficial Effects of Social Networking Sites. In Proceeding of CHI 2010, 1749-1752.

Toma, C. L., Hancock, J. T., & Ellison, N. B. (2008). Separating fact from fiction: Deceptive self-presentationin online dating profiles. Personality and Social Psychology Bulletin, 38, 1023 - 1036.

Tufte, E. (1983). The Visual Display of Quantitative Information. Graphics Press.

Ubisoft Ent. (2009). Assassin’s Creed Web Battle. Retrieved on July 20, 2010 from www.assassinscreed.com/webbattle/.

Valve Corp. (2003). Steam.

van Hoorn, N., Togelius, J., and Wierstra, D., and Schmidhuber, J. (2009). Robust player imitation with multiobjective evolution. Proceedings of IEEE Congress on Evolutionary Computation.

Walther, J. B. (2007). Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition. Computers in Human Behavior, 23, 2538-2557.

Weber, B. and Mateas, M. (2009) A Data Mining Approach to Strategy Prediction. IEEE CIG Symposium 2009.

Weiner, B. (1995). Intrinsic motivation. In A. Manstead, M. Hewstone, S. Fiske, M. Hoggs, H. Reis, & G. Samin (Eds.), The Blackwell encyclopedia of social psychology. Cambridge: Blackwell.

Williams, D., Yee, N. and Caplan, D. (2008). Who Plays, How Much, and Why? A Behavioral Player Census of Virtual World. Journal of Computer Mediated Communication, 13, 993 - 1018.

Yee, N. (2006). Motivations of Play in Online Games. CyberPsychology and Behavior, 9(6), 772-775.

Zynga. (2009). Farmville. [Internet].


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