Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Community
Ask the community for help and clear up your study doubts
Discover the best universities in your country according to Docsity users
Free resources
Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors
Describes in this theory human coomunication to gain the knowledge and understanding.
Typology: Thesis
1 / 57
This page cannot be seen from the preview
Don't miss anything!
By Carolyn E. Costa A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science Communication At The University of Wisconsin-Whitewater December, 2015
Introduction “Play is more than a mere physiological phenomenon or a psychological reflex... .It is a significant function... .All play means something” (Huizinga, 1950, p. 1). What play means can be difficult to determine, and what makes it fun can be even more difficult to define, and may vary from individual to individual, but Huizinga (1950) identifies several characteristics that define play. By these characteristics, play is voluntary, it is separate from “real” life, it is limited in terms of time and space, it has rules, and it tends to create social groups and communities based on play that exist even when the game ends. Although these attributes were defined many years before video games and online games existed, they still apply to online games today. For example, one chooses to play games and which games to play; it is voluntary. Dragons, aliens, and other mythical monsters that may exist in the game worlds do not exist in “real” life, therefore it is separate. Events or quests which may take place in online games often have time limits, and are restricted to the virtual space created by the game developers; certain actions or behaviors may not be allowed in the game. For instance, End User License Agreements may list behaviors that game moderators may “ban” players for engaging in. And those who play online games may form friendships through this medium, join guilds, and communicate outside of the game. But how can one better understand this in- game communication?
In recent years, the number of people who play games, as well as those who specifically play online games, has climbed dramatically (e.g. Longman, O’Connor, & Obst, 2009; Petitte, 2012; Satter, 2013; Soper, 2013). At its height of popularity, World of Warcraft, perhaps one of the more well-known Massively Multiplayer Online (MMO) games, was reported to have between 11.5 and 12 million players (Longman et al., 2009; Satter, 2013); it is only one of many MMO games currently available. Petitte (2012) estimated that there were approximately 400 million MMO players in 2012, and in 2013 an estimated 700 million people played online games (Soper, 2013). However, while popular opinion may suggest that most gamers are male, the Entertainment Software Association (ESA) has found that females comprise approximately 44% of the gaming population (ESA, 2015). Studies do not always reflect this ratio (e.g. Frostling-Henningsson, 2009; Greitmeyer & Cox, 2013; Gitter, Ewell, Guadagno, Stillman, & Baumeister, 2013; Herodotou, Kambouri, & Winters, 2014): some lean toward almost all male participants, while others may include more than 50% females. There is a large amount of variance in regards to representation of the sexes in games studies, and findings which indicate both behavioral and communicative differences (e.g Dino, 2010; Kuznekoff & Rose, 2013); clearly this is an important variable to consider. With so many players in online games, both male and female, there is a large amount of communication that takes place in this context, as well
often include those other than task-oriented or game-based topics (Peña & Hancock, 2006). The government has acknowledged for years the importance of in-game communications (Satter, 2013). In 2013, it was revealed that both U.S. and U.K. government agents have been monitoring in-game communications in recent years in an effort to uncover information on terrorists and other criminals who might be using in-game messaging systems to communicate (Satter, 2013). The agents watched for suspicious communications in games like Second Life and World of Warcraft. Furthermore, game designers and those in the game industry are beginning to investigate how to design MMOs with more social elements; Christou, Law, Zaphiris, and Ang (2013) surveyed individuals involved in game design to gather their thoughts on how game design can support sociability within the game using open-end questions. Christou et al. (2013) identified three categories of sociability, which included in-game communication. The results also showed that sociability is an important aspect of Massively Multiplayer Role-Playing Games (MMORPGs), but it was found that none of the respondents used specific methods to incorporate structures for sociability within games. As part of the study, several groups where formed and asked to discuss game design options that could increase social opportunities in games based on the results of the survey. One of the groups, which focused on general game aspects to promote sociability instead of a specific game concept, emphasized that “any
social game should include an advanced chat interface, which would allow holding conversations with several people as well as include channels for general chat” (p. 731). Christou et al.’s (2013) study on sociability in games demonstrates that the game industry recognizes the importance of communication and socializing in games, and, although more research is required, is trying to find ways to incorporate that into game design. Investigating how individuals communicate within games and testing whether established communication theories apply to these environments could aid the game industry in this endeavor by providing more research on the topic. This would help both academics and professionals better understand how players interact in games, and potentially help game designers incorporate sociability structures that would make their games more appealing to players. As previously mentioned, communication in online games can be used for discussions that are not solely based on the game (Peña & Hancock, 2006; Satter, 2013), and as such there can be some blurring of the lines Huizinga (1950) described that set the game space apart from “real” life. This raises more questions for communication scholars to investigate, such as whether existing communication theories can be applied to game environments, whether players wish to reduce uncertainty in regards to others with whom they interact, which strategies may be used, and whether factors such as age, sex, or game experience
Literature Review Uncertainty Reduction Theory. Developed by Berger and Calabrese in 1975, URT was intended to provide a communication-based perspective to help explain and predict interpersonal communication behavior. Berger and Calabrese (1975) explained that other research in the field at that time focused more on social psychology theories than communication, and so they sought to construct an explanation that directly focused on interpersonal communication. Since it was first developed, URT has been tested extensively and successfully applied to various contexts, including computer-mediated communication (CMC) situations (e.g. Antheunis, Valkenburg, & Peter, 2010; Palmiere, Prestano, Gandley, Overton, & Zhang, 2012). In URT, uncertainty is defined as the inability to predict another person’s responses or behavior (Berger & Calabrese, 1975), or a lack of information (Yoo, 2009). URT assumes that each person’s responses and behaviors are based in part on how he or she predicts the other person will behave and respond, though rules and social or cultural norms also play a role (Berger & Calabrese 1975). These rules or norms may be implicit in that the individual cannot state the rule, but still follows it, or explicit, where the individual can state both the rule and the reason for adhering to it. When two strangers first meet, neither is able to predict very much about the other; therefore both experience this type of uncertainty and may attempt to reduce it (Berger & Calaberes, 1975). This becomes the main goal of the initial
interaction, to become better able to predict how the other person will choose to behave, which in turn helps each communication partner better determine how she or he will behave. Communication partners may participate in proactive uncertainty reduction, or retroactive uncertainty reduction, according to URT. Proactive means trying to make predictions before the other person acts, while retroactive involves attempts to explain the other person’s response after the person has acted or spoken. Although the theory was originally intended to focus on the prediction of responses in the initial interactions between strangers, it has since been expanded, and includes three potential phases of relationships: entry, personal, and exit (Berger & Calabrese, 1975). The entry phase begins with the interaction of two strangers and explains how they attempt to reduce uncertainty about each other. In the personal phase, the communicators share information on values, attitudes, and personal problems. Indeed, communicators may even begin touching on some of these topics toward the end of the entry phase, such as attitudes and opinions that are considered low risk. The exit phase is defined as the point at which communicators decide whether it is desirable to continue the interaction in the future. However, there is no set time at which each phase begins or ends; the entry phase may last several minutes, or continue over several separate interactions with the same communication partner. Likewise, the phases
1990; Bradac, 2001). The motivation to reduce uncertainty may be attributed to factors such as whether future interactions are anticipated (Kellermann & Reynolds, 1990), which is also more logical than emotional. Kellermann and Reynolds (1990) also found that uncertainty can have a positive relationship with information-seeking behavior, but only when the level of uncertainty surpasses people’s tolerance for uncertainty. Both the definition of uncertainty and the motivations to reduce it are described as more strategic than emotional (Bradac, 2001). Uncertainty reduction is described as an intellectual activity, not one that is engaged in so that individuals will feel less discomfort from not knowing (Bradac, 2001), although it seems likely that the level of tolerance would involve emotions to some extent, and one source points out that uncertainty can result in “stress and anxiety” (Berger, 1987, p. 54). The point of intolerance mentioned by Kellermann and Reynolds (1990) seems to suggest a point at which the lack of predictability, combined with other factors such as motivations, would create feelings of discomfort or anxiety that the individuals would wish to relieve by engaging in information-seeking behaviors to reduce uncertainty. There are several different strategies which may be used to reduce uncertainty in social contexts, namely passive, active, and interactive strategies (Berger, 1979; Baxtor & Wilmot, 1984; Berger, 1987; Neuliep & Grohskopf, 2000). In passive strategies, the potential communication partner may be observed,
preferably in an environment with fewer social rules, in order to gauge how she or he responds to others. The environment itself may also provide cues about the person being observed; Berger and Calabrese (1975) use an example of a political rally, which would provide cues regarding the attitudes the individual held towards politics and possibly even a certain candidate. These cues would serve to reduce the level of uncertainty by providing potential topics to discuss that would most likely be deemed safe, or would have responses that were more predictable. Asking others about the potential communication partner is an example of active information-seeking (Berger, 1979). This method also includes actions that are more involved than simple observation, but do not include direct contact with the individual. Interactive strategies are those such as directly communicating with or questioning the individual. Although URT was intended to apply to face-to-face communication, studies have shown that individuals also use these strategies in online communications (e.g. Antheunis et al., 2010; Gibbs, Ellison, & Lai, 2011; Palmieri et al., 2012; Ramirez, Walther, Burgoon, & Sunnafrank, 2002). However, strategies may be used in differing degrees and in different forms. Antheunis et al. (2010) found that on social networking websites, passive strategies were the most commonly used, followed by interactive and active. Passive strategies were used by almost 99% of participants, while approximately 84% used interactive and
fourth type of uncertainty reduction strategy considered unique to CMC and labeled as extractive, although of the four strategies it is the least used (Ramirez et al., 2002; Gibbs et al., 2011). Combined, it has been shown that individuals apply these four strategies and attempt to reduce their uncertainty when communicating with others online in social contexts. Games and communication. Despite the number of recent studies involving video games, there remains the question of how a communication theory will function in a game environment, since play involves “a stepping out of ‘real’ life into a temporary sphere of activity with a disposition all of its own” (Huizinga, 1950, p. 8). While many studies focus on violence in games (e.g Hollingdale & Greitemeyer, 2013; Fischer, Kastenmüller, & Greitemeyer, 2010; Barlett, Branch, Rodeheffer, & Harris, 2009), few have focused on communication (e.g. Peña & Hancock, 2006; Kuznekoff & Rose, 2013), which is an important aspect of gaming (e.g. Christou et al., 2013; Satter, 2013). Communication in games is regarded as one of the main sources of sociability in games by some game designers (Christou et al., 2013), and can be a motivation for gamers to play (Frostling-Henningsson, 2009). In addition, some game studies allude to variables which may influence communication in games, such as age and sex; one study directly investigated how the sex of participants can influence game communication (e.g. Kuznekoff & Rose, 2013). Many of the studies conducted on games have investigated violence
and behavior, and have had mixed results (e.g. Adachi & Willoughby, 2011; Barlett, Branch, Rodeheffer, & Harris, 2009; Ferguson & Reuda, 2010; Fischer, Kastenmüller, & Greitemeyer, 2010; Gitter et al., 2013; Greitemeyer et al., 2012; Greitemeyer, 2013; Hollingdale & Greitemeyer, 2013). Hollingdale and Greitemeyer (2013) found that playing violent video games with personalized avatars increased aggression levels, much like Fischer, Kastenmüller, and Greitemeyer’s (2010) results, which showed that personalized avatars increased player identification with the avatar which lead to increased aggression in the participants of the study. Barlett et al. (2009) also found that violent games increased aggressive behavior, but results showed that effect was limited in duration; it took four minutes or less for participants’ aggressive thoughts and feelings to revert back to their pre-established baselines, and five to ten minutes for aggressive behavior to abate. Another study found that violent games increased players’ perceptions of negative human traits in themselves, but playing prosocial games, increased feelings of positive human traits in the player (Greitemeyer, 2013), possibly by making aggressive thoughts less accessible (Greitemeyer et al., 2012). However, the relationship between the effects of violent and prosocial games is more complicated than it might first appear. Gitter et al.’s (2013) results showed that prosocial content within a violent game could reduce aggression and increase prosocial thoughts, while Ferguson and Reuda’s (2010) study found
build relationships and friendships online with those who share similar interest; since gaming is often a social activity, many players communicate often with others in the game (Herodotou, Kambouri, & Winters, 2014). Individuals may play games as a form of companionship and social support derived through communications with other players (Longman, O’Connor, & Obst, 2009). Frostling-Henningsson (2009) found that communication can be an important motivation for many gamers to play. Peña and Hancock (2006) may have done the most focused study on in-game communication to date in an effort to determine whether in- game communication was mostly task-oriented or whether it would include relational communication, such as might occur in face-to-face situations. The study recorded text-based communication within a multiplayer game over a two-week time span, gathering over five thousand messages. Participants were unaware they were being recorded until after recording was completed. The researchers then categorized and analyzed messages, using guild rank (or lack of guild associations) to assess the participants’ experience levels. They found that in-game communications included significantly more socioemotional communication than task communications (Peña & Hancock, 2006). Socioemotional communication is comprised of the expression of personal information and emotions, while task communication involves offering suggestions regarding aspects of the game and asking for more task-related information.
Peña and Hancock’s (2006) results are comparable to Frostling- Hennsingsson’s (2009) findings, which showed that communication in games may involve different levels of communication, from discussions regarding game rules to conversations about real world problems and personal issues. “The communication that takes place when gaming online occurs seems to be of utmost importance for many gamers,” the results stated (Frostling-Henningsson, 2009, p. 558). Peña and Hancock’s (2006) results also showed that participants were more likely to communicate positive than negative messages to other players, where negative messages included disagreement, antagonism, and profanity (Peña & Hancock, 2006). Negative messages were more likely to originate when other players were not polite, broke social norms, or when complications related to in-game tasks emerged. Peña and Hancock (2006) also determined that experience with games has an effect on in-game communication. Players with more experience were more likely to communicate positive message more often than those with less experience (Peña & Hancock, 2006). Gamers with more experience were also more likely to use specialized language, e.g. abbreviations and emoticons. Sex. In 1996, Emmers and Canary found that sex may influence which URT strategy is chosen; their results showed that males were more likely to use interactive strategies, while females were more likely to use passive strategies.
