Abstract Trouble in River City: The Social Life of video games by

Choosing Appropriate Theories

A social learning approach would recognize that the social aspect of game play is plainly different than the social aspect of more traditional media and must be accounted for carefully. Compared to traditional passive media, observation modeling in games may stem from at least three sources. First, players may observe and model the behavior of computer-driven characters. This kind of observational learning is what has been tested in prior studies. Secondly, players in a multiplayer game will also observe and potentially model the behaviors of other players in the virtual space. This modeling may well differ from observation of computer-controlled characters. Would a player process an aggressive character action differently if she knew the character was controlled by an actual human being rather than software? The research has not addressed the possibility. This distinction is especially salient because as games incorporate more players, game content is driven increasingly by actions among the players themselves. Lastly, social learning may occur from play that occurs in physical proximity, as in an arcade, home or office, in Internet cafés, or in LAN tournaments. In this case, the in-game interactions and observations occur in parallel with real-world ones. Studies that proceed without allowing for these distinctions may well have been testing players in highly unnatural settings, and conflating various sources of effects. Sherry, for example, suggests that because the typical game experience is social, the dominant format of laboratory studies on solo game players playing against a computer may be testing for an effect that does not occur normally (J. Sherry, 2003; J. Sherry & Lucas, 2003).

An alternative approach is to use cultivation theory to generate hypotheses and research questions. The most well-known application of cultivation theory (Gerbner, Gross, Morgan, & Signiorelli, 1980) has been vigorously assailed on both methodological and analytical grounds. Some have attacked the spurious causal claims derived from correlational methods, or the study’s lack of control (Hirsch, 1980). Others assail the theory not for method, but because it fails to explain exactly how cultivation occurs. In response, Shrum (1999) has theorized that cultivation is essentially an extension of well-established models of cognitive processing dealing with memory recall. Cultivation effects occur through memory recall when someone uses heuristic processing (Chaiken, 1987) rather than central processing of information (Chaiken, Liberman, & Eagly, 1989; Petty & Cacioppo, 1981). These heuristic shortcuts can lead to a distortion of reality because they emphasize accessible information that may be incorrect rather than harder-to-recall correct information. The likelihood of such a shortcut over the central route can in part be predicted by the decision rule (Tversky & Kahneman, 1973), which “posits that people infer the prevalence of a construct from the ease with which an example is retrieved (i.e. its accessibility from memory). That is, they infer that because something is easy to remember, it must occur frequently” (Shrum, 1999)(p. 126). Cultivation operates by repeating a series of constructs to a viewer, making those constructs easier to remember. Someone who watches a lot of violence may therefore infer incorrectly that the real world is more violent than it actually is because those images are most readily available. When thinking about the level of violence in the real world, images of televised violence are more likely to guide perceptions when the person has been exposed to a lot of those images.

Shrum’s cultivation theory offers a helpful framework for research into online worlds, and not only for violence. If the theory holds true, people who participate in some online activity may find it easier to remember a construct from their online experience, and may incorrectly associate that construct with their offline experience. The more exposure to the online world someone has, and the more realistic it is, the easier it should be to infer that constructs from that world occur in the real one. One particularly compelling reason to use Shrum’s theory lies in the nature of some online games. The world of a video game can range from a simple two-dimensional and unrealistic static screen to a highly detailed and immersive three-dimensional environment. According to Shrum’s approach, a highly immersive and realistic game world, such as will be examined here, should affect how players perceive their everyday surroundings. A challenging test of this theory would then be a very specific prediction based on the particular characteristics of the game world and whether or not they affect perceptions of the real world. Specific aspects of the real world emphasized in the game world should influence a subjects’ view of reality; but aspects of the real world not present in the game world should have no influence. A design that can establish causality is also necessary to validate a cultivation approach.

The research community has focused on children. Given the consistent findings for the negative effects of television on children, it is understandable that researchers would seek to provide empirical data to inform concerned policy makers and consumers. Also, the public rhetoric on gaming has declared that “games are for kids” and that adult players are deviants. However, by following these discourses and ignoring the actual demographics of players, researchers have missed the boat. The foremost example of this phenomenon is an over-reliance on very young subjects in experiments. While exploring issues of children and game violence remains important, it is also important to study other ages, especially when the average age of game players is steadily increasing for both home consoles and online play. Those under 18 now make up only 42% of console players and only 28% of PC players.¹ Data from the 2002 Pew Internet and American Life Project show that 37% of all Internet users have played a game online, including an astounding 38% of people over 65 (Pew, 2002). Because the effect size from television violence is thought to be much lower for adults (Paik and Comstock, 1994), we can speculate that this may also be true for video games. Still, samples should match the actual population.

The Challenge of Method

To date, game research has relied on two methods, the survey and the laboratory experiment. Surveys are open to the plausible alternative explanation that what has been found is correlational rather than causal. For example, Dominick (1984) found that boys who played a lot of arcade games watched more violent television. But the survey method he used cannot determine whether television viewing caused game play, vice versa, or if some third variable such as parental influence caused both. Laboratory studies have drawbacks as well, especially when considering the social nature and duration of game play in natural settings. Research suggests that the length of the game play stimulus is a vital factor even in the studies investigating short-term effects. In his meta-analysis, Sherry (2001) noted that there were two studies of one particular game (Mortal Kombat) with different durations. In the first study, undergraduates played the game for 10 minutes, and the researchers concluded that their higher levels of aggression were due to game play (Ballard & Weist, 1995). In the second study, undergraduates played the same game for 75 minutes, and the researchers found almost no effects (Hoffman, 1995). As Sherry concluded, the initial effects might have been caused by arousal that wore off and was replaced by boredom or fatigue, neither of which is thought to increase aggression.

Arousal has stimulated learning and long-term aggressive cognitions in television research (L. Huesmann, 1999), but this link has not been established for games. Experiments like Hoffman’s question the presence of such a link. Laboratory-based experiments on games and aggression have also been assailed as unduly artificial and not representing the typically social context of game play (Goldstein, 2001). This last point is especially salient, given that 60% of gamers now play with friends and 25% play with a spouse or parent (State of the Industry Report 2000-2001, 2001). A longitudinal study would help triangulate the findings, and reach the type of sustained effects Huesmann found for television. Regardless of their individual expectations, each of the four major reviews came to the same conclusion. To quote Anderson and Bushman, “longitudinal research is badly needed” (C. A. Anderson & Bushman, 2001)(p. 359).

The Choice of Stimulus

The last problem is one that has received little attention in the research to date, but is equally, if not more, important than the others. This is the issue of the choice of stimulus in the experiment, and what can be said afterwards. Only recently have researchers begun to measure important variables that relate to the content of the game under study. Few researchers have noted the distinctions between basic game genres or play contexts. Previously, researchers had picked a game based on their own prima facie understanding of it as “violent,” or “non-violent.” An exception is Anderson and Dill, who have been among the few to pretest their stimuli to rate it on their dimensions of interest (C. A. Anderson & Dill, 2000). The distinction between games in an issue not to be glossed over. Indeed, the wide variety of video game content and play experiences would likely surprise most first-time investigators. The online database www.allgame.com lists descriptions of 35,400 different games across 93 different game machines plus computers. Even if we could make the assumption that all of these games are uniform in their level of violence (or some other variable), we would still be left to account for the wide variety of play contexts that include place and social environment: at home, school, work, in an arcade, on a cell phone, alone, with a few others, with a small crowd, or online with several thousand others.

To collapse this wide variety of content and context into a variable labeled “game play” is the equivalent of assuming that all television, radio or motion picture use is the same. As Dill and Dill have noted, “This is akin to lumping films like The Little Mermaid with Pulp Fiction, and expecting this combined ‘movie viewing’ variable to predict increases in aggressive behavior” (Dill & Dill, 1998)(p. 423). For this reason, it is essential to have a full understanding of a game before choosing a research design. Correspondingly, the conclusions drawn from the experiment in the next chapter are not intended to generalize to anything like “games,” or “violent games,” which are too gross-level a qualification for rigorous research. What follows is a discussion of the game genre, its players and its culture, and an in-depth participant observation study of a game prior to the main study. What kind of game genre does it represent? What is the content like? Who typically plays such games and why? What social issues and effects present themselves through game play? This exercise provided crucial insight into the content and context of the game world.

Massively Multiplayer Games, and the People Who Love Them

This dissertation now focuses on a video game called Asheron’s Call 2, typically referred to as AC2 by its players. Studying any one video game demands that the researcher not only understand the particular game, but also understand where that game fits in the total universe of all games. Otherwise, the issues of generalizability and external validity are essentially ignored. Therefore, this study of AC2 begins by placing it in the context of other games and by describing how it is similar to or different from other titles. AC2 will be shown to be representative of a particular class of online games known as “massively multiplayer role playing games,” or MMRPGs.

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