نوع شناسی کاربران دنیای مجازی اجتماعی بر اساس انگیزش
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|30048||2014||9 صفحه PDF||سفارش دهید||7947 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers in Human Behavior, Volume 33, April 2014, Pages 330–338
The past years have witnessed a rapid increase in the use of social media networks, including virtual worlds, across broad segments of Internet users. Several researchers have investigated the motivations behind social media use, however, few studies have attempted to explain the use of free-form/social virtual worlds (SVWs). Using both, qualitative and quantitative approaches, the current study aims to identify these motives and classify SVW users according to motivation-based user segments. Furthermore, the current paper examines the link between SVW users’ motivations and their demographics. Our findings suggest that SVW users are motivated to use the platform seeking the following: ‘Friendship’, ‘Escapism’, and ‘Role-playing’; followed by ‘Achievement’, a ‘Relationship’ and ‘Manipulation’. Seven types of SVW users were identified based on their motivations, namely, ‘Role-Players’, ‘Relationship Seekers’, ‘Manipulators’, ‘Achievement Seekers’, ‘Friendship seekers’, ‘Uninvolved’, and ‘Escapists’. Users’ motivations to use the platform differ based on their ‘age’ and ‘gender’, and some notable differences in demographics among user types were identified.
Virtual worlds (VWs) are three-dimensional (3D) environments in which users either have a goal to achieve, called “game-oriented” VWs (e.g., World of Warcraft), or are left free with no specific goal imposed by the VW, called “free-form” or “social” VWs (SVWs), such as There and Second Life (Bainbridge, 2007). According to VW research firm KZero (2012), in the fourth quarter of 2011, the total number of registered users of VWs amounted to 1700 million people. In Second Life (SL) alone, 36 million users are currently registered, including more than 1 million active users (Linden Lab, 2013). There are not only a lot of users of VWs, but also a lot of hours are spent in-world. For instance, during the last 10 years, SL users spent the equivalent of 217,266 years of time in-world (Linden Lab, 2013). While some previous studies have examined users’ motivations for using game-oriented VWs (e.g., Bartle, 1996 and Yee, 2006), few studies have attempted to explain the motivations for using SVWs. As up until now only qualitative inquiries on the subject have been conducted, the focus of the current study is to identify SVW users’ motivations employing both qualitative and quantitative approaches. This will allow us to (1) determine the prevalence of the SVW motivations identified, (2) classify SVW users according to motivation-based user segments, and (3) explore the link to user demographics, such as gender. SVWs are 3D environments that mimic the real world to a large extent, allowing for live interactions between users’ avatars and providing unlimited possibilities and experiences. Users are empowered to freely create and control their environment. Users can create, buy, and sell products and services, marry, dance, eat, and so forth; that is, they can live a whole virtual life. SVWs also possess their own currency, which is exchangeable for real-life currencies, making VWs a viable economy. These characteristics have attracted the attention of several different entities, who explore these VWs and use them for different purposes. Many real world businesses, for instance, are increasingly having a presence in SVWs to build their brands, and/or to grow their revenues (Arakji & Lang, 2008). Universities, political parties, international organizations, and even embassies can be found in VWs. To successfully achieve their objectives, understanding SVW users is crucial. This has urged researchers to study avatars and their in-world behavior (e.g., Andrade, 2009, Guo and Barnes, 2009, Banakou and Chorianopoulos, 2010, Hassouneh and Brengman, 2011 and Lam and Riedl, 2011). SVWs also provide an interesting platform for researchers to conduct experiments, carry out observations, and analyze economic markets and social networks (Bainbridge, 2007). Castronova (2006) demonstrated that VWs are effective and attractive venues for conducting social science studies. The current study aims to extend our understanding of VW users using qualitative and quantitative approaches. Motivations for using SVWs are first explored qualitatively by means of in-depth interviews with 20 active SL users. Subsequently, a survey is carried out among 455 active SL users to assess the prevalence of these motivations and classify users based on their motivations. Furthermore, the current paper examines if a link exists between users’ motivations and their demographics (e.g., gender). This paper is organized as follows: first, related literature from the social media field is reviewed and the objectives of the current study are presented. Subsequently, the methodologies used for the qualitative and the quantitative studies are explained thoroughly. The results of both studies are then reported and discussed. Finally, some limitations are addressed and some topics for future research are suggested.
نتیجه گیری انگلیسی
5. Results 5.1. Qualitative study results Based on the in-depth interviews, six motivations were identified behind the use of SVWs: ‘socializing’, ‘fun-seeking/gratification’, ‘real-life purpose’, ‘role-playing’, ‘compensation seeking’, and ‘free self expression’. In this section, the motivations revealed for using the VW SL are explained and discussed in relation to related literature. 5.1.1. Socializing This motivation refers to using the VW to socialize and meet people from around the world. It is about making friends and talking about personal issues. One respondent noted: “I have some very special irreplaceable people.” For some users this is an initial reason for joining the platform, but not necessarily their reason for remaining in-world. When asked about his reason for being in SL, one male respondent answered: “Socializing mostly but I am starting to use it for work.” The ‘social’ motivation was also revealed in previous qualitative research on motivations for using SVWs ( Jung and Kang, 2010 and Zhou et al., 2011) and participating in social media, including game-oriented VWs (e.g.: Bartle, 1997 and Yee, 2006). 5.1.2. Fun-seeking/gratification This motivation refers to joining the VW to relax, get away from one’s real-life problems, and have fun, enjoying the in-world activities and experiences. Related statements included: “Recently divorced, I am here to relax,” “I love the music and dancing so I keep coming back,” “Mostly I enjoy the shopping here, then talking, then seeing new places” “Eventually it [being in SL] is a thrill.” This motivation is similar to the ‘amusement’ motivation found by Jung and Kang (2010) and the ‘experiential’ values revealed by Zhou et al. (2011). 5.1.3. Real-life purpose This motivation refers to using the VW to meet a ‘real-life purpose’, such as attending an in-world course, conducting research, working and improving one’s real-life income, and so forth. One respondent mentioned: “I am trying to learn how to build educational Sims… history in particular, allowing students to experience events and buildings in history.” Another respondent stated: “I am here [in SL] to promote my band and our music.” Jung and Kang (2010) also identified ‘knowledge acquisition’ and ‘financial’ reasons for joining SVWs, which was supported by Zhou et al. (2011) who noted ‘functional values’ for using SVWs. 5.1.4. Role-playing This motivation refers to enjoying being someone else in-world, different from one’s real character/role. “It is fun being someone different here,” “I play here to explore parts of life I wouldn’t really do in reality.” Some VW users play a character in-world that is very different from their real-life character/role or they can even play several characters by owning more than one avatar. One respondent noted: “I have another alt toon [avatar] on here that plays in Victorian era role-play.” This is similar to the ‘role playing’ aspect of the ‘immersion’ motivation to use game-oriented VWs, where users enjoy story-telling and creating characters that fit into these stories ( Yee, 2006). 5.1.5. Compensation seeking This motivation refers to joining the VW to achieve one’s dreams and potential. For some users, the VW is seen as a second chance to live their lives the way they always wished. People who are not able to make their dreams come true in the real world reside in the SVW to live their dreams. Related statements included: “People have a jet-set life here, what we cannot have in real-life,” “I have got to have this body in SL, so it’s easier to wear the clothes I wish I could wear in real-life,” “I can live like a millionaire.” Living their dream in the SVW can fulfill Maslow’s ultimate needs for ‘self-esteem’ and ‘self-actualization’, which refer to desires for confidence, competence, mastery, adequacy, achievement, and growth ( Goble, 1970). The compensation strategy introduced by Adler (1917) suggests that one will try, consciously or unconsciously, to cover up feelings of inferiority or unfulfilled desires. Thus, for those who cannot achieve their full potential in real-life, the VW offers another chance to fulfill this need. Hence, they can realize their dreams in the VW rather than in the real world. 5.1.6. Free self expression This motivation refers to joining the SVW to freely express oneself, being liberated from RW social/ethical and/or cultural restrictions. A single father noted: “I can wear anything here; in RL, I have to be more frugal and a bit more selective and conservative in style.” “Things I would not do or wear in RL I am free to do/wear in SL.” Respondents also felt free in the kinds of relationships they can form in-world. In previous research, the ‘need for self expression’ (i.e. the need to present one’s identity to other people) was also found to influence participation intentions in virtual communities ( Han, Zheng, & Xu, 2007), as well as users’ perceptions of real money trade in massively multiplayer games ( Lehdonvirta, 2005). 5.2. Quantitative study results 5.2.1. Exploratory factor analysis The 41 items measuring the motivations behind using SVWs were subjected to a principal components factor analysis with varimax rotation to reveal the underlying dimensions. While 10 factors were extracted with an eigen value over 1, the scree plot indicated a 6 factor solution to be adequate. We, thus, opted to run the analysis for 6–10 factor solutions. Initially, the 8 factor solution seemed to provide a good starting point, explaining almost 60% of the total variance. Items were carefully inspected for domain representation and items that loaded less than 0.5 on any factor or exhibited high cross-loadings were dropped. Initially two items were deleted because of low loadings: “I find SL relaxing” and “People who role-play extensively bother me.” Another item that exhibited high cross-loadings on two factors was also deleted: “I am in SL to enhance my real-life income.” The remaining items were resubmitted for another factor analysis. A seven-factor solution was extracted at this point, as in the previous solution after item deletion, one of the factors was left with only one item. Again three items had to be deleted due to low loadings (<.5): “In SL, I am living my dream life away from any real-life money constraints,” “I enjoy being my true self in SL,” and “I am mainly in SL for a real-life purpose (e.g., for school).” Two more items (that constituted a factor) were deleted as their content did not represent a logical factor (“I am in SL to meet people from around the world,” and “I enjoy the fact that in SL I can live free of any real-world restriction”). A six-factor solution was then extracted and two further items (“SL allows me to live the way I wish I could in real life,” and “I am the same person in both lives: SL and in real life”) were deleted (factor loadings <.5). A final 6-factor model was estimated with the remaining 31 items. The factor solution exhibited a KMO measure of sampling adequacy of .821 and accounted for almost 61% of the total variance. All communalities ranged from .407 to .875. Table 1 illustrates the 31-item factor structure. Table 1. Exploratory factor analysis results. Factor Items Manipulation Friendship Achievement Role playing Escapism Relationship I like to manipulate other people so they do what I want them to in SL .832 .027 .075 .084 −.029 .046 I scam other people out of their items or money in SL .825 −.027 .019 .011 −.064 .108 I beg for money or items from other users in SL .760 .003 .079 .014 −.058 .097 I like to dominate other people in SL .724 .091 .034 .178 .027 .052 I like to taunt or annoy other SL residents/users .717 −.034 .045 .015 .063 .043 I like to spy on other SL residents .657 −.100 .097 .036 .129 .061 I talk to my SL friends about personal issues .001 .811 .048 −.035 .173 .104 I have made some good friends in SL −.128 .798 .021 .012 .177 .003 I find myself having meaningful conversations with others in SL .020 .766 .026 .073 .048 −.048 Friends in SL have offered me support when I had a real life problem or crisis −.032 .764 .035 .013 .206 .142 The main reason I am in SL is to socialize −.024 .630 −.142 .063 .251 .039 It is very important to me to have a lot of friends in SL .124 .530 .130 .031 .165 .264 Running a successful business in SL is very important to me .021 .095 .838 .022 −.023 .071 Owning my own business in SL is very satisfying .005 .054 .826 .007 −.012 .003 It is very important to me to have created one of the best creations in SL .150 −.030 .738 .019 −.014 .036 I enjoy building and creating things in SL −.153 .006 .712 .043 −.001 .010 I try to gain as much money as possible in SL .188 −.074 .702 .061 .040 .098 I like to feel powerful in SL .376 .060 .607 .144 .102 .056 I like to try out new roles and personalities with my character/s .078 −.006 .030 .848 .157 .001 I enjoy playing a different character in SL .032 −.039 .036 .838 .173 −.089 I enjoy being someone different in SL .063 −.064 .104 .762 .227 −.051 I make up stories and histories for my character/s .128 .117 −.018 .726 −.011 .101 I like the feeling of being part of a story .028 .123 .088 .696 .028 .090 I like the escapism aspect of being in the virtual world −.065 .054 .008 .116 .782 −.039 Being in SL lets me forget some of the real problems that I have .065 .193 .029 .150 .755 .102 Being in SL lets me vent and relieve stress from the day .025 .188 .049 .032 .718 −.027 I am in SL to relax from my real life responsibilities and/or problems .041 .095 .009 .116 .696 .111 I wish I had my avatar body in real life −.009 .215 −.023 .073 .572 .164 In SL,I find myself free in the kind of relationships I have .050 .323 −.022 .079 .522 −.089 I am in SL to find a real life partner .217 .154 .133 −.014 .033 .886 I am in SL to find love .187 .166 .101 .078 .160 .871 Cronbach Alpha/Pearson R .846 .842 .844 .849 .799 .790 Values in bold represent the structure of each factor. Table options 5.2.2. Motivations for using social virtual worlds A one-way between-subjects ANOVA with post-hoc comparisons using the Tukey HSD test indicated significant mean differences in the potency of each of the identified SVW usage motivators (F (5, 2724) = 510, p < .001), except for the main two. As shown in Graph 1, the highest rated reasons/motivations for using SVWs are ‘Friendship’ (M = 3.70; SD = .760) and ‘Escapism’ (M = 3.69; SD = .719), followed by ‘Role-Playing’ (M = 3.14; SD = .919) and ‘Achievement’ (M = 2.80; SD = .896). ‘Relationships’ (M = 1.98; SD = 1.04) and ‘Manipulation’ (M = 1.53; SD = .665) are found to motivate SVW users in general to a lesser extent. Full-size image (14 K) Graph 1. Motivations for using social virtual worlds according to gender. Figure options Independent samples t-tests were conducted to compare the SVW use motivations between males and females. Male SVW users appear to be significantly more driven by ‘Manipulation’ compared to females (males: M = 1.63, SD = 0.703, vs. females: M = 1.44, SD = 0.614; t(435.7) = 3.08, p = 0.002). Male SVW users are also more motivated by ‘Relationships’ than female users (males: M = 2.09, SD = 1.04, females: M = 1.88, SD = 1.03; t(453) = 2.13, p = 0.033). Also the ‘Achievement’ factor seems to motivate male users somewhat more than female users (males: M = 2.88, SD = 0.872, females: M = 2.72, SD = 0.912; t(453) = 1.83, p = 0.069). Female SVW users, on the other hand, report to be significantly more motivated by ‘Friendship’ than their male counterparts (males: M = 3.52, SD = 0.758, females: M = 3.86, SD = 0.728; t(453) = −4.77, p < 0.001), and by a drive for ‘Escapism’ (males: M = 3.48, SD = 0.724, females: M = 3.89, SD = 0.657; t(453) = −6.3, p < 0.001). No significant difference was found between male and female SVW users with respect to their motivation for ‘Role playing’ (t(453) = 0.023, p = 0.982). 5.2.3. Social virtual world user typology In a second step, we sought to identify clusters of users with distinctive motivations for using SVWs. To this end, we employed a two-step clustering procedure using both hierarchical and non-hierarchical methods (cf. Arnold & Reynolds, 2003). First, the factor scores representing the six motivations for using SVWs were submitted to a hierarchical cluster analysis (Ward’s method, squared Euclidian distances). In a second step, we conducted a K-means cluster analysis using the hierarchal cluster centers (Hair et al., 1998, Jamal et al., 2006 and Milligan, 1980). As this study is the first to identify the different types of users in free-form/SVWs based on motivations, we opted to test a range of cluster solutions (3–7). The 7-cluster solution (see Table 2) produced the most interpretable results with ANOVA indicating significant mean differences in user motivations across the 7 clusters. Table 2. Clusters’ motivations. Relationship seekers Role players Manipulators Friendship seekers Escapists Uninvolved Achievement seekers Motivations Manipulation −0.49368 −0.38936 1.84545 −0.36031 −0.13695 −0.28114 −0.1124 Friendship 0.33249 0.26546 0.16056 0.54541 −1.847 −0.31467 0.44397 Achievement −0.16182 0.54409 −0.05661 −1.29749 −0.20985 −0.06658 0.92878 Role Playing −0.07345 0.99186 0.13772 −0.2468 0.02245 −0.26338 −1.05288 Escapism 0.34246 0.12238 −0.13819 0.26137 0.5748 −1.59527 0.38001 Relationship 1.53713 −0.34522 0.10195 −0.56105 −0.12888 −0.11405 −0.45004 Values in bold represent the motivations where a cluster scores the highest or lowest in comparison to other clusters. Table options Cross tabulations were also conducted, relating SVW users’ cluster membership with their demographic characteristics. Chi-square tests reveal that the clusters have significantly different: age distributions (χ2(df = 12) = 24.513, p = .017), gender constitutions (χ2(df = 6) = 13.476, p = .036), SL usage frequency (χ2(df = 18) = 57.302, p < .001), number of avatars owned (χ2(df = 6) = 25.159, p < .001) and SL job ownership (χ2(df = 6) = 25.218, p < .001) (see Table 3 and Graph 2, Graph 3 and Graph 4). Table 3. Socio demographics of social virtual worlds’ users. Sample (%) Relationship seekers (%) Role players (%) Manipulators (%) Friendship seekers (%) Escapists (%) Uninvolved (%) Achievement seekers (%) Pearson Chi square Age 16–29 38 40 48 48 35 22.6 30.5 32 .017 30–49 46 46 34 46 47 54.7 45.8 58 50–70 16 14 18 6 18 22.6 23.7 10 Gender .036 Males 48 45 45 60 37 49 63 42 Females 52 55 55 40 63 51 37 58 Having an SL job <.001 Yes 25 25 36 26 17 6 19 37 No 75 75 64 74 83 94 81 63 SL usage frequency <.001 A couple of times a year 9 3.2 3.4 7.7 6.7 19.6 24.6 4.9 Every month 12 11.3 8 16.9 11.7 25.5 12.3 3.3 Every week 29 29 27.3 29.2 26.7 33.3 22.8 36.1 Every day 50 56.5 61.4 46.2 55 21.6 40.4 55.7 SL experience .115 Up to 2 years 22 35.4 18.7 26.2 21.7 17 22 12.9 3–4 years 63 53.8 65.9 66.2 56.7 66 57.6 72.6 Over 5 years 15 10.8 15.4 7.7 21.7 17 20.3 14.5 No. of avatars <.001 One 40 27.4 25.3 44.6 41.4 52.8 58.6 35.5 More than 1 60 72.6 74.7 55.4 58.6 47.2 41.4 64.5 Significant differences in cluster membership within the socio-demographic variables are in italic. Table options Full-size image (17 K) Graph 2. Social VW user typology distributed by gender. Figure options Full-size image (18 K) Graph 3. Age constitution of SVW user groups. Figure options Full-size image (17 K) Graph 4. Clusters’ SL usage frequency. Figure options The clusters found are briefly described below and are ordered based on their respective sizes (see Graph 2): 22.214.171.124. Role players (Cluster size: 91, Percentage: 20.0%) As can be expected, these SVW users score highest on ‘Role playing’, enjoying being someone different from their real-life character. They are the heaviest users of SL and around 75% of them own more than one avatar, the highest percentage among all clusters; 36% of them also have an SL job. This cluster is almost equally composed of males and females, who are mostly young. 126.96.36.199. Relationship seekers (Cluster size: 65, Percentage: 14.3%) These SVW users score highest on ‘Relationship’, seeking a real-life partner, and/or love and lowest on ‘Manipulation’. They are heavy users of SL, with over 56% of them logging into SL on a daily basis. This cluster is equally composed of males and females and is particularly represented among more recent SVW users. Remarkabl, more than 72% of them own several avatars. 188.8.131.52. Manipulators (Cluster size: 65, Percentage: 14.3%) Scoring highest on ‘Manipulation’, these SVW users like to manipulate other users and to scam them out of their money or items. This cluster is composed of somewhat more moderate users of the VW and contains mainly young males. 184.108.40.206. Achievement seekers (Cluster size: 62, Percentage: 13.6%) Scoring highest on the ‘Achievement’ factor and lowest on the ‘Role-playing’ dimension, these SVW users are in SL to conduct their own business, to create and/or to make money. As can be expected, the highest percentage of SL job ownership is found in this group (37%). This cluster is composed of rather heavy users of SL with some experience and includes somewhat more middle-aged females. 220.127.116.11. Friendship seekers (Cluster size: 60, Percentage: 13.2%) Scoring highest on ‘Friendship’ and lowest on ‘Achievement’, these SVW users are in SL to make good/close friends and to have meaningful conversations with them. Females are particularly well represented in this cluster of generally heavy SL users of which only 17% own an SL job. 18.104.22.168. Uninvolved (Cluster size: 59, Percentage: 13.0%) Scoring low on all factors and the lowest on the ‘Escapism’ factor, these users do not seem to enjoy any aspect of the SVW. They spend less time in-world, with almost 25% of them using SL only a couple of times a year. This group is mainly composed of males and they mainly own only one avatar (58.6%). 22.214.171.124. Escapists (Cluster size: 53, Percentage: 11.6%) Scoring highest on the ‘Escapism’ factor and very low on everything else, especially on the ‘Friendship’ factor, these SL residents use the VW to escape from their real-life problems and stress. They log into the VW less frequently than the rest of the users and most of them do not have an SL job. This cluster is equally composed of males and females, who are mostly older. Cross tabulations with Chi-square tests reveal some significant differences in cluster membership according to gender χ2(df = 6, N = 455) = 13.48, p = .036). More specifically, there seem to be significantly more ‘Manipulators’ among males (17.7%) than among females (11.1%); χ2(df = 1) = 4.120, p = .042. We also discover more ‘Uninvolved’ SL users among males (16.8%) than among females (9.4%); χ2(df = 1) = 5.598, p = .018. On the other hand, more ‘Friendship Seekers’ can be found among females (16.2%) than among males (10.0%); χ2(df = 1) = 3.779, p = .052. With regards to age, cross tabulations with Chi-square tests reveal that there are significantly less ‘Manipulators’ among the eldest age group (8.8%) than among the younger age groups (18% and 17% respectively) χ2(df = 2) = 6.748, p = .034. On the other hand, among the elder SVW users more ‘Escapists’ can be identified than in the younger age groups (17.1%50–70y versus 10.7%30–49y and 7%50–70y; χ2(df = 2) = 8.561, p = .014. More ‘Role Players’ are apparent among the youngest age group (25.6%) than among the older age groups 15.2%30–49y and 17.6%50–70yχ2(df = 2) = 5.555, p = .062.