Abstract Trouble in River City: The Social Life of video games by
Download 6.01 Mb.
|
- Navigate this page:
- Problem Two: Multiple Internet Uses
- Problem Three: Exploring Complex Dynamics On- and Offline
- Learning from Prior Research
Problem One: Time DisplacementTraditional time displacement approaches to Internet use ignore changes that occur online. What was appropriate for traditional media does not automatically apply to new media. When television cut into movie attendance, radio or newspaper usage, it was a straightforward exercise in applying diffusion curves and inferring displacement; it made perfect sense to succinctly show how new media took time from old media because both were sources of entertainment (DeFluer, 1972). But while such analyses are attractive, they often omit other important variables. For example, DeFleur did not factor in the demographic upheavals of the 1950s; instead of seeing that many young families with infants preferred the convenience of home entertainment, he assumed that the changes must have been primarily a result of the new technology itself. Direct displacement analysis is also problematic for newer media, but for different reasons. For the study of the Internet, the chief obstacle is even more fundamental than social factors: TV and the Internet are not functionally equivalent (Kestnbaum et al., 2002) because the Internet’s uses are broader than television’s. And because the Internet may be more interactive than television, we cannot assume that its social use is analogous. If Internet users might be more engaged or more social with their fellow users than television viewers (or less), it is not appropriate to apply the same analytical framework. In their review of Internet studies to date, DiMaggio et al concluded “The functional equivalence model that described the effects of television thus far appears not to fit the experience of Internet users” (DiMaggio et al., 2001)(p. 315). Therefore, the difference between optimists and pessimists is in their functional view of the Internet—whether it is displacing or substituting, or creating something wholly new. For those who do not believe that Internet-based communication should ever be (or should always be) considered an adequate substitute, displacement is the only possible way of thinking. For those who consider more complex dynamics, there are interesting questions to consider. Maybe Internet time displaces face-to-face time. Maybe it doesn’t. The key point is that we do not know whether total social activities are or are not in decline. After all, some of that time online will be given to sociability. If we make the simple mistake of equating all time online to be isolated and passive like television—something problematic enough on its own (E. Katz, 1996; Robert Kubey, 1996)—we preclude the possibility that there can be any gains there to make up for offline losses, or that something more complex might be taking place. Likewise, we cannot assume that all time online is contributing to a vibrant social universe. Clearly, sociability online and offline could be qualitatively different, but since we have little grasp on how this functions, no researcher should insist that they are sure the Internet has this or that impact. What we have seen so far are only the marginal totals. We have not seen anything resembling their underlying change tables to see where the churn may be. Dertouzos asks the most fair question: “Which qualities of human relationships will pass well through tomorrow’s information infrastructures and which ones will not?” (Dertouzos, 1997) Such an approach stresses functional displacement, rather than only time displacement. Problem Two: Multiple Internet UsesEarly evidence suggests that Internet use varies by age, gender, education and psychological profile; different types of people use the Internet for different things (Howard et al., 2001). Because of this, patterns of use are a more profitable route to explore than gross hours of use (Shah et al., 2001). Typologies of users and their preferences have begun to bear fruit (Norris, 1998). Women, for example, are more likely to play games, research health information and look for new jobs. Young people are more likely than old to keep current with popular culture online and participate in chat sessions. On an individual level, we have evidence that online behaviors also vary by psychological profile (McKenna, Green, & Gleason, 2002). These differences suggest that it is inappropriate to consider Internet use as a monolithic, singular concept. Not only are the use patterns different from user to user, the content is the most varied in any medium in history. For example, Bimber argues that gross-level Internet usage is too muddled an activity for studying civic engagement (Bimber, 2000). The next steps in uses and effects research should be in talking about specific types of people using specific parts of the Internet; we should not lump chat rooms, stock quotes, sex sites, news gathering, and games all in the same category of stimulus. “It is a mistake to collapse use that includes activities as varied as playing EverQuest, telecommuting, reading the news, and emailing next door neighbors into global measures such as time online” (Baym et al., 2002). Once we have adequate measures, “Internet usage” will be too coarse a unit of analysis (Ben Anderson & Tracey, 2001). At that point, it will be appropriate to measure the impact of chat rooms, email, online video games, or other specific activities. Problem Three: Exploring Complex Dynamics On- and OfflineHow then, should we measure sociability in an online world? We should start by acknowledging that sociability and social capital effects can occur offline and online (Mandelli, 2002), and that online social networks are real: When a computer network connects people or organizations, it is a social network. Just as a computer network is a set of machines connected by a set of cables, a social network is a set of people (or organizations or other social entities) connected by a set of social relations, such as friendship, co-working, or information exchange (Garton, Haythornthwaite, & Wellman, 1999). We do not know much about what kinds of sociability occur, but it should at the very least be included in any discussion of whether some specific Internet use, in conjunction with daily life, is isolating or engaging, or somehow both. We need to be taking parallel measures of sociability online and offline, and to think through how those realms might differ, and we need an approach that works equally well for both. “Weak tie” (bridging effects) and “strong tie” (bonding effects) thinking provides that approach. If we think that weak- and strong-tie networks will look and behave differently, we are faced with the prospect of measuring both their presence and their effects. The kind of network present must be established, and then whether there are social capital gains to be had through it. For a measure of tie strength, Granovetter’s original work suggested using frequency of contact, separated at more or less than twice per week, (Granovetter, 1973). But what is it that makes a tie strong or weak? Simple frequency of contact collapses the dimensions of affective bonds into quantity. A detested co-worker might look like a stronger tie than a weekend poker buddy. Clearly, there are more dimensions to be incorporated. The best guidance comes from Marsden and Campbell, who found that the two primary underlying factors of tie strength were intensity and duration. They found through survey testing that both factors can be predicted by the degree of closeness one person feels for another (Marsden & Campbell, 1984). Separate from the strength of the tie is a measure of the kind of social capital that the tie generates, or, stated another way, the effects of the tie. A laudable first effort by Norris (2002) focused exclusively on the type of network created rather than on the effects such a network might have. Absent were distinctions between online and offline life, measures of emotional support, access to information, affective bonds for fellow group members or outsiders, and several other theorized phenomena to be discussed shortly. The work did support Haythornthwaite’s intuitions about the usefulness of the Internet for weak-tie networks. Chapter 6: Being Massive: Understanding Online Games As noted in the previous chapter, one of the biggest obstacles in Internet research has been in testing for the effects of a monolithic “Internet.” This chapter follows the advice of Shah et al (2001) in exploring particular kinds of Internet behaviors and activities, and by linking this effort to the study of video games. The first half of this dissertation examined how games have been represented in the media, contrasting media frameworks with games’ actual use. This chapter begins by focusing on the research agenda that resulted from those views. Despite good work, gaps remain. There is an important distinction to be made here: pointing out gaps in the research is very different from saying that there are no effects of video games. As the final chapters will illustrate, there certainly are effects. A careful study of a game must remain separate from the social discourses surrounding game use. This chapter will illustrate that approach in two ways: by placing a game and its players in a real social context, and by presenting the results of an in-depth participant observation of a game. This sets the stage for hypotheses and an experiment in the next chapter. Learning from Prior ResearchWhat lessons can we draw from the research on games to date? Much like the research on TV, movies and radio, the research agenda for games has been influenced directly by the discourse that surrounds a new communication technology. As a result, the majority of the research—still scant and inconclusive after 20 years of intermittent study—has focused on the potential negative effects of game play, chiefly those relating to aggression and violence. For Internet-based games, there is even less: “there is little research on even the most basic aspects of online gaming” (M. D. Griffiths, Davies, & Chappell, 2003)(p. 90). The main limitations in the research have been a reliance on older theories developed for passive media, studying populations that are not always representative, and a paucity of causal data. These may explain in part why the field has produced inconsistent findings regarding the negative effects of game play. Because research into game violence and aggression is rooted firmly in the more established field of media effects (Funk, 1993), researchers have drawn on a series of theories and approaches that have established what most consider to be a reasonable link between television violence and real-world aggression. Following this tradition, game researchers have expected to find stronger links than with television because of the more active level of participation in game. However, while some studies have found connections between game violence and aggression (Ballard & Weist, 1995; Bushman & Anderson, 2002; Irwin & Gross, 1995; Schutte, Malouff, Post-Gordon, & Rodasta, 1988), others have not (J. Cooper & Mackie, 1986; Graybill, Kirsch, & Esselman, 1985; D. Scott, 1995), and researchers remain divided (M. D. Griffiths, 2000; Wiegman & Schie, 2000). Several recent reviews and meta-analyses of the video game research literature have come to different conclusions while pointing out serious shortcomings in the literature. Sherry’s meta-analysis (2001) suggests that games increase aggression, and that this effect is likely smaller than television’s. However, Sherry added the proviso that the varying findings, treatment times, stimuli and subject pools prevent a truly clear understanding of effects. Treatment times have varied from five to 75 minutes, and have consisted of “violent” content ranging from crude box-like shapes in an early 1980s boxing game (Graybill et al., 1985) to highly realistic 3D hand-to-hand combat (Ballard & Weist, 1995). A review by Anderson and Bushman reached the conclusion that exposure to violent video games is linked with aggression, but they noted the absence of longitudinal studies from the analysis (C. A. Anderson & Bushman, 2001). Two other reviews of the literature (Dill & Dill, 1998; M. Griffiths, 1999)—from the same journal—reached opposite conclusions about the strength of the findings to date. In the first, Dill and Dill refrained from doing a meta-analysis at all due to a scarcity of research. Instead, they suggested that the literature points to aggression effects, but that the key shortcomings are a lack of longitudinal methods and an over-reliance on minors as subjects of study. Griffiths (1999) also found fault with the research’s reliance on young subjects. Additionally, he suggested that the wide range of available games have been largely ignored as having potentially different effects, a theme to be taken up shortly. In sum, researchers suspect a strong linkage between violent games and aggression, but with the exception of relatively short-term effects on young adults and children, they have yet to demonstrate this link conclusively.
Download 6.01 Mb. Share with your friends:
|