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1、<p>  字?jǐn)?shù):英文2580單詞,12686字符;中文4087漢字</p><p>  出處:Sang Yup Lee. Interpersonal influence on online game choices[J]. Computers in Human Behavior, 2015, 45: 129-136.</p><p><b>  外文文獻(xiàn): </

2、b></p><p>  Interpersonal influence on online game choices</p><p>  Abstract Several theories stress the importance of interpersonal influence on an individual’s adoption of a product or ser

3、vice. However, there has been little research that empirically examined how online friends influence an individual’s online product choices. This study examines the effect of a game player’s online friends who adopted a

4、game earlier than the player on the likelihood that the player adopts the game. Two main factors considered in this study are: (1) the number of online frien</p><p>  Key words: Interpersonal influence; Onli

5、ne product choices; Online casual games; Hazard model </p><p>  1.Introduction</p><p>  There is no established definition of an online causal game, yet online casual games usually refer to onli

6、ne video games developed for mass consumption even for those who would not normally regard themselves as a ‘gamer’ (International Game Developers Association (IGDA), 2009). Online casual games possess certain characteris

7、tics in common: they are easy to learn; they require a small amount of time to be played; and online casual game players play casual games mainly for fun and relaxation (IGDA</p><p>  A typical online casual

8、 game portal site has several social features. On an online casual games portal site, game players can be friends with other players. In this study, a game player’s friends on a game portal site are defined as other play

9、ers whom the player is directly connected to on the portal site. Game players are motivated to become friends with other game players and interact with them, because there are many games that encourage collaboration amon

10、g game players and competing (or play</p><p>  These social features of online casual games portal sites and the accessibility on these portal sites of critical data on game players’ relationships and intera

11、ctions with others, their game choices, and their gaming behaviors make it possible to examine the influence of interpersonal interaction on players’ game choices.</p><p>  For this study, we look at a parti

12、cular online casual games portal site, Kongregate.com. Kongregate started its service in 2006 and it is one of the most visited online casual game portal sites in the U.S. With its growth, Kongregate was acquired by Game

13、stop (an American video game retailer) in 2010. Kongregate provides online game players with a variety of casual games, which are developed by either professional game developers or other players who use Kongregate. As o

14、f Feb, 2014, there were 80</p><p>  This paper studies how a player’s Kongregate friends influence the player’s game choices on Kongregate. In this study, game players with whom a player has direct connectio

15、ns on Kongregate are referred to as the player’s Kongregate friends. On Kongregate, a player can directly connect with another player by clicking a ‘friend’ button linked to that person.</p><p>  This study

16、specifically examines the effect of the number of a player’s Kongregate friends who adopted a particular game earlier on the likelihood that the player will adopt2 the game. According to Rogers’ diffusion of innovations

17、theory (2003), the number of an individual’s friends who adopted a product or service earlier can influence the person’s decision whether or not to adopt the product or service, because interpersonal interactions can be

18、an important source of information about a produc</p><p>  In addition to the number of Kongregate friends who adopted a game earlier, we also consider the closeness of the relationships on Kongregate betwee

19、n a player and her Kongregate friends who adopted the game earlier, because it is possible that the influence of a Kongregate friend on a player’s game adoption decision can vary with the relational closeness between the

20、 player and her friend. In other studies (e.g., Bakshy, Hofman, Mason, & Watts, 2011; Christakis & Fowler, 2007) it was found that t</p><p>  In this study, we focus on game players who have register

21、ed on Kongregate, because only for registered players can information about gaming behavior, game adoptions, and Kongregate friends be collected. Furthermore, because only a registered player can make connections with ot

22、her Kongregate players, unregistered players are not suitable for studying influences of Kongregate friends on game choices. That registered players are examined in this study also means that the results of this study ca

23、nno</p><p>  2.Statistical model and data</p><p>  2.1.Hazard model</p><p>  In this study, we use the proportional hazard model introduced by Cox in 1972 to study the effect of the

24、 number of a player’s Kongregate friends who adopted a game before day t on the likelihood that the player adopts the game on that day. We also ask how the effect of a Kongregate friend who adopted a game earlier on the

25、likelihood that the player adopts the game varies with the strength of the tie between the player and that friend. For this, we include the number of a player’s prior adopter f</p><p>  As mentioned above, w

26、e also include other independent variables; (1) the frequency with which the player adopts new games, (2) how often the player plays games on Kongregate, and (3) whether the genre of the game is the player’s favorite gen

27、re. Finally, in order to control for factors unique to a game that can influence its adoption, we include a game fixed effect variable, which might reflect the game’s genre, popularity, quality, and difficulty.</p>

28、<p>  Our model includes both fixed and time-varying independent variables. Fixed variables are those whose values do not change during the 5 days following a player’s first visit to the site since a game’s releas

29、e, whereas time-varying variables are those whose values change during these 5 days.</p><p><b>  2.2.Data</b></p><p>  For this study, we used data for randomly selected registered g

30、ame players on Kongregate because information such as games played and listings of Kongregate friends can only be collected for registered players. We downloaded a list of registered game players who were playing games o

31、n Kongregate at least twice a day during the week of 3/24 (Sun) to 3/30 (Mon), 2013. The original dataset had 17,858 game players. Because this size of dataset is too big to be handled by social network analysis stati<

32、;/p><p>  We collected data on game adoptions for those 1,668 game players and their Kongregate friends for two games, (1) Mystery IQ Test, and (2) Live Puzzle as in Table 1. The genre of ‘Live Puzzle’ is puzzl

33、e and that of ‘Mystery IQ Test’ is brain. A puzzle game is a game that requires a player to put pieces together in a way that meets the goal of the game. A brain game is a game in which a player uses logic to accomplish

34、the tasks. A puzzle game can be a sort of a brain game. ‘Mystery IQ Test’ incorp</p><p>  Table 1 Information about games examined in this study</p><p>  For a game to be included in this study,

35、 the game had to provide at least one task right after its release so that players could earn points by accomplishing the task. Among all the games released on Kongregate during a month-period, from 4/9/2013 to 5/8/ 2013

36、, only the two games above met this requirement.</p><p>  For players in the sample, we first checked whether a game player played any games on Kongregate during the 7 days after each game’s release. For tho

37、se who played games during the 7 days, we collected information about when they first visited the site since each game’s release and whether they adopted each of the games in Table 1 during the 5 days following their fir

38、st visits. Then, we collected the data on game adoptions for their Kongregate friends.</p><p>  3.Summary and conclusion</p><p>  In this study, we examined the effect of the number of a player’

39、s Kongregate friends who adopted a game earlier on the likelihood that the player adopts the game. In addition to the effect of the number of a player’s Kongregate friends who adopted a game earlier, we also asked how th

40、e strength of the ties between a player and her Kongregate friends who adopted a game earlier was associated with the likelihood that the player adopts the game.</p><p>  We found that the effect of the numb

41、er of Kongregate friends who adopted a game earlier on a player’s adoption of the game was positive, but statistically insignificant whether those prior adopter friends had a reciprocal tie with the player. This finding

42、suggests that the importance of interpersonal influence on product choice posited by several theories such as diffusion of innovations theory (Rogers, 2003) and theory of planned behavior (Ajzen, 1991) is not strongly su

43、pported in online casual</p><p>  In this study, we only considered the effect of the number of Kongregate friends who adopted a game earlier on a player’s game adoption. As found in other studies (e.g., Uga

44、nder et al., 2012), however, other characteristics of a player’s personal network composed of her prior adopter Kongregate friends such as the number of clusters, may exert more influences on the player’s game adoption t

45、han the number of the player’s friends. Thus, in the future studies, other characteristics of a player’s pe</p><p>  This study has some limitations. First, genres of the games examined in this study were br

46、ain and puzzle. It is possible that the influence of Kongregate friends on a player’s adoption of a game varies with the genre of the game. Second, the two games examined in this study were both single player games. The

47、statistically insignificant influences of Kongregate friends on a player’s adoption of those two games might be because those games are single player games. Thus, in the future studies, it i</p><p>  The res

48、earch questions were examined in the context of online casual games. But it is likely that interpersonal influence on an individual’s game adoption decision is different from interpersonal influence on an individual’s ad

49、option decisions for other online products. Thus, in future studies, in order to extend our understandings about how an individual’s online product choices or adoptions are influenced by her online friends, the research

50、questions asked in this study should also examined in</p><p><b>  中文譯文:</b></p><p>  人際關(guān)系對(duì)網(wǎng)絡(luò)游戲選擇的影響</p><p>  摘要 一些理論強(qiáng)調(diào)人際影響對(duì)個(gè)人選擇產(chǎn)品或服務(wù)的重要性。然而,從根本上來(lái)說(shuō),關(guān)于網(wǎng)絡(luò)朋友如何影響個(gè)人的網(wǎng)絡(luò)產(chǎn)品選擇的研

51、究很少。本研究考察了游戲玩家的網(wǎng)絡(luò)朋友對(duì)其選擇游戲的影響,其網(wǎng)絡(luò)朋友可能早就玩過(guò)此款網(wǎng)絡(luò)游戲。本研究考察的兩個(gè)主要因素是:(1)較早玩游戲的網(wǎng)絡(luò)朋友數(shù)量;(2)玩家與較早玩游戲的網(wǎng)絡(luò)朋友之間的聯(lián)系強(qiáng)度。本研究選擇了一個(gè)包含1668名游戲玩家的游戲活動(dòng)和關(guān)系數(shù)據(jù)的風(fēng)險(xiǎn)模型,我們發(fā)現(xiàn):(1)玩家較早玩某種游戲的網(wǎng)絡(luò)朋友越多,他選擇這種游戲的可能性就越大;(2)較早玩游戲的網(wǎng)絡(luò)朋友對(duì)玩家選擇游戲的可能性的影響,會(huì)隨著玩家和網(wǎng)絡(luò)朋友之間的聯(lián)系強(qiáng)

52、度而變化。</p><p>  關(guān)鍵詞:人際影響;網(wǎng)絡(luò)產(chǎn)品選擇;網(wǎng)絡(luò)休閑游戲;風(fēng)險(xiǎn)模型</p><p><b>  1.簡(jiǎn)介</b></p><p>  雖然網(wǎng)絡(luò)休閑游戲還沒(méi)有一個(gè)確切的定義,但通常來(lái)說(shuō),網(wǎng)絡(luò)休閑游戲是指為了大眾消費(fèi)而開(kāi)發(fā)的網(wǎng)絡(luò)視頻游戲,即使對(duì)于通常不認(rèn)為自己是“玩家”的人來(lái)說(shuō)也是如此(國(guó)際游戲開(kāi)發(fā)者協(xié)會(huì)(IGDA),2009)

53、。網(wǎng)絡(luò)休閑游戲具有某些共同的特征:它們易于學(xué)習(xí);需要少量的時(shí)間來(lái)玩;玩家玩休閑游戲主要是為了樂(lè)趣和放松(IGDA,2009)。網(wǎng)絡(luò)休閑游戲通過(guò)幾種不同類(lèi)型的平臺(tái)如PC上的Web瀏覽器(例如,通過(guò)網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站和社交網(wǎng)站)、控制臺(tái)、智能手機(jī)和平板電腦提供給游戲玩家。本研究側(cè)重于網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站,這是因?yàn)椋海?)網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站提供了一個(gè)合適的背景,可以很好地考察網(wǎng)絡(luò)朋友對(duì)游戲選擇的影響;(2)它們是最常用的網(wǎng)絡(luò)休閑游戲訪(fǎng)問(wèn)平

54、臺(tái)之一(劉,2013);(3)從網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站收集本研究所需的數(shù)據(jù)比從其他網(wǎng)絡(luò)休閑游戲平臺(tái)收集數(shù)據(jù)更容易。</p><p>  一個(gè)典型的網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站有幾個(gè)社交功能。在一個(gè)網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站上,游戲玩家可以和其他玩家交朋友。在本研究中,游戲玩家的好友在游戲門(mén)戶(hù)網(wǎng)站上被定義為其他玩家,其他玩家可以直接連接到門(mén)戶(hù)網(wǎng)站上。游戲玩家被鼓勵(lì)與其他游戲玩家成為朋友,并與他們進(jìn)行互動(dòng),因?yàn)橛性S多游戲鼓勵(lì)游戲玩家

55、之間進(jìn)行合作,與其他人競(jìng)爭(zhēng)(或玩)會(huì)更有趣,并與其他玩家成為朋友,這很容易讓玩家之間進(jìn)行合作與互動(dòng)。一旦游戲玩家成為另一個(gè)玩家的朋友,玩家可以通過(guò)他們之間的專(zhuān)用通信渠道與朋友聊天。此外,玩家可以觀(guān)察他的朋友在網(wǎng)站上做了什么以及正在做什么。因此,玩家的游戲行為有可能在網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站上受到他的朋友的影響。</p><p>  網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站的這些社交功能,以及這些門(mén)戶(hù)網(wǎng)站對(duì)游戲玩家關(guān)系和互動(dòng)、他們的游戲選

56、擇和游戲行為的關(guān)鍵數(shù)據(jù)的可訪(fǎng)問(wèn)性,使得能夠考察到人際互動(dòng)對(duì)玩家的游戲選擇的影響。</p><p>  對(duì)于這項(xiàng)研究,我們來(lái)看一個(gè)特定的網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站Kongregate.com。Kongregate于2006年開(kāi)始服務(wù),是美國(guó)最受歡迎的網(wǎng)絡(luò)休閑游戲門(mén)戶(hù)網(wǎng)站之一。隨著其成長(zhǎng),Kongregate于2010年被Gamestop(美國(guó)電玩游戲零售商)收購(gòu)。Kongregate為網(wǎng)絡(luò)游戲玩家提供了各種休閑游戲,這些

57、游戲是由專(zhuān)業(yè)游戲開(kāi)發(fā)商或Kongregate的其他玩家開(kāi)發(fā)的。截至2014年2月,該網(wǎng)站上共有80,747個(gè)游戲,截至2012年,該網(wǎng)站注冊(cè)用戶(hù)數(shù)為6,970,697人次。</p><p>  本文研究了一個(gè)玩家的Kongregate朋友如何影響玩家在Kongregate上的游戲選擇。在這項(xiàng)研究中,游戲玩家與Kongregate有直接聯(lián)系的玩家被稱(chēng)為玩家的Kongregate朋友。在Kongregate上,玩家可

58、以通過(guò)單擊與此人鏈接的“好友” 按鈕直接與其他玩家建立聯(lián)系。</p><p>  這項(xiàng)研究專(zhuān)門(mén)探討了玩家通過(guò)特定游戲的Kongregate朋友的數(shù)量對(duì)玩家將選擇游戲的可能性的影響。根據(jù)羅杰斯的創(chuàng)新擴(kuò)散理論(2003),較早選擇產(chǎn)品或服務(wù)的朋友數(shù)量可能會(huì)影響該人決定是否選擇該產(chǎn)品或服務(wù),因?yàn)槿穗H交往可以是一個(gè)產(chǎn)品的重要信息來(lái)源,一個(gè)人對(duì)產(chǎn)品的態(tài)度可能會(huì)受到人際互動(dòng)的影響。但只有少數(shù)研究對(duì)這個(gè)主題進(jìn)行了實(shí)證檢驗(yàn)(例如

59、,班迪耶拉和拉蘇爾,2006)。即使在那些研究離線(xiàn)情況下人際關(guān)系對(duì)個(gè)人產(chǎn)品選擇的影響的文獻(xiàn)中,也沒(méi)有看到早期選擇產(chǎn)品的朋友或熟人的數(shù)量如何影響到人們選擇它的決定。這主要是因?yàn)樵陔x線(xiàn)設(shè)置中,很難收集一個(gè)人的朋友或熟人中有多少選擇某種特定產(chǎn)品以及何時(shí)選擇產(chǎn)品的數(shù)據(jù)。然而,可以在 Kongregate 上收集有關(guān)游戲選擇的個(gè)人級(jí)別的數(shù)據(jù),通過(guò)較早玩游戲的 Kongregate 朋友的數(shù)量,來(lái)預(yù)測(cè)玩家的游戲選擇情況。</p>&l

60、t;p>  除了較早玩游戲的Kongregate朋友的數(shù)量外,我們還考慮到一個(gè)玩家和他較早玩游戲的Kongregate朋友之間的Kongregate關(guān)系的親密度,因?yàn)橐粋€(gè)Kongregate朋友對(duì)玩家選擇游戲的可能性影響會(huì)隨著玩家和的朋友之間的關(guān)系的親密度而變化。在其他研究中(例如,巴克什,霍夫曼,梅森和瓦特,2011;克里斯塔基斯和福勒,2007),發(fā)現(xiàn)個(gè)人的行為受其他人影響的程度隨著與他人的關(guān)系密切程度而變化。在這項(xiàng)研究中,兩

61、名玩家之間的親密關(guān)系是指他們之間的聯(lián)系強(qiáng)度。兩個(gè)人之間的聯(lián)系強(qiáng)度是一個(gè)時(shí)間數(shù)量、情感強(qiáng)度、親密程度和互惠服務(wù)的功能(格蘭諾維特,1973,第1361頁(yè))。在社交網(wǎng)絡(luò)文學(xué)中,兩個(gè)人之間的聯(lián)系強(qiáng)度通常以溝通互惠的程度、共同朋友的數(shù)量和互動(dòng)頻率來(lái)衡量(吉爾伯特和Karahalios,2009)。對(duì)于這項(xiàng)研究,兩名玩家之間的聯(lián)系強(qiáng)度是通過(guò)是否相互配合來(lái)衡量的。</p><p>  在這項(xiàng)研究中,我們專(zhuān)注于在Kongreg

62、ate注冊(cè)的游戲玩家,因?yàn)橹挥袕淖?cè)的玩家那兒才能收集到關(guān)于游戲行為、游戲收藏和Kongregate朋友的信息。此外,由于只有注冊(cè)的玩家可以與其他Kongregate玩家建立聯(lián)系,未注冊(cè)的玩家不適用于研究Kongregate朋友對(duì)游戲選擇的影響。在這項(xiàng)研究中,注冊(cè)的玩家也意味著這項(xiàng)研究的結(jié)果不能推廣到?jīng)]有在Kongregate注冊(cè)的游戲玩家身上,因?yàn)樽?cè)和未注冊(cè)的游戲玩家可能會(huì)有差異。例如,比起未注冊(cè)的玩家,注冊(cè)的玩家可能會(huì)更加認(rèn)真地對(duì)

63、待他們的休閑游戲,會(huì)更加頻繁地玩更多的游戲。</p><p><b>  2.統(tǒng)計(jì)模型和數(shù)據(jù)</b></p><p><b>  2.1.風(fēng)險(xiǎn)模型</b></p><p>  在本研究中,我們選擇了考克斯在1972年引入的比例風(fēng)險(xiǎn)模型來(lái)研究在第t天之前選擇游戲的玩家的Kongregate朋友的數(shù)量對(duì)玩家在當(dāng)天選擇游戲的可能

64、性的影響。我們還會(huì)思考,較早玩游戲的Kongregate朋友對(duì)玩家選擇游戲的可能性的影響,會(huì)隨著玩家和那個(gè)朋友之間的聯(lián)系強(qiáng)度而變化。為此,我們的研究涉及到較早玩游戲的和玩家有聯(lián)系強(qiáng)度的Kongregate朋友的數(shù)量,以及較早玩游戲而和玩家沒(méi)有聯(lián)系強(qiáng)度的Kongregate朋友的數(shù)量,這兩種數(shù)量作為主要的獨(dú)立變量。</p><p>  如上所述,我們還包括其他自變量:(1)玩家選擇新游戲的頻率;(2)玩家在Kong

65、regate上玩游戲的頻率;(3)游戲的類(lèi)型是否是玩家最喜歡的類(lèi)型。最后,為了可以控制影響游戲選擇的獨(dú)特因素,我們選擇了一個(gè)可以反映游戲類(lèi)型、流行度、質(zhì)量和難度的游戲固定效應(yīng)變量。</p><p>  我們的模型包括固定和時(shí)變的自變量。固定變量是指玩家在游戲發(fā)布后第一次訪(fǎng)問(wèn)站點(diǎn)的5天內(nèi)值不變的變量,而時(shí)變變量則是指在5天內(nèi)變化的變量。</p><p><b>  2.2.數(shù)據(jù)&l

66、t;/b></p><p>  對(duì)于這項(xiàng)研究,我們使用隨機(jī)選擇的注冊(cè)游戲玩家在Kongregate上的數(shù)據(jù),因?yàn)橹荒苁占?cè)玩家的游戲和Kongregate朋友列表等信息。我們下載了2013年4月23日(星期天)到4月30日(星期一)的一天內(nèi)至少兩次在Kongregate上玩游戲的注冊(cè)游戲玩家列表。原始數(shù)據(jù)集有17,858名游戲玩家。因?yàn)檫@個(gè)規(guī)模的數(shù)據(jù)集太大,不能及時(shí)通過(guò)社交網(wǎng)絡(luò)分析統(tǒng)計(jì)軟件包進(jìn)行處理,而且

67、收集所有17,858名玩家及其Kongregate朋友的游戲行為和游戲選擇的數(shù)據(jù)(玩家的Kongregate朋友的平均人數(shù)在樣本中約為60人)將非常耗時(shí),所以我們使用隨機(jī)數(shù)字生成器,從這17,858名游戲玩家中隨機(jī)選擇了2,000名玩家。在這2,000名玩家中,只有1,668名公開(kāi)了自己的個(gè)人資料,至少有一個(gè)朋友被選定為研究對(duì)象。最終樣本中玩家的Kongregate朋友的平均數(shù)量為61人。</p><p>  我

68、們收集了1,668名游戲玩家和他們的Kongregate朋友在兩場(chǎng)游戲中的數(shù)據(jù),如表1所示的(1)解密測(cè)試和(2)即時(shí)拼圖。即時(shí)拼圖的類(lèi)型是益智游戲,解密測(cè)試的類(lèi)型是大腦智商測(cè)試游戲。拼圖游戲是要求玩家把碎片整合在一起,以達(dá)到目標(biāo)的一種游戲。解密測(cè)試是要求玩家使用邏輯來(lái)完成任務(wù)的一種游戲。拼圖游戲可以是大腦智商測(cè)試游戲中一個(gè)小的類(lèi)型。解密測(cè)試除了包括語(yǔ)言測(cè)驗(yàn)和數(shù)學(xué)題外, 還包含了其他幾種類(lèi)型的任務(wù)。</p><p&g

69、t;  表1本研究中所考察的游戲信息</p><p>  在這項(xiàng)研究中,游戲在發(fā)布后必須至少提供一項(xiàng)任務(wù),以便玩家可以通過(guò)完成任務(wù)來(lái)獲得積分。在 Kongregate 發(fā)布的所有游戲中的一個(gè)月期間,從2013年4月9日到2013年5月8日,只有上述兩種游戲符合這一要求。</p><p>  對(duì)于樣本中的玩家,我們首先檢查了游戲玩家是否在每個(gè)游戲發(fā)布后的7天內(nèi)在Kongregate上玩過(guò)該游

70、戲。對(duì)于那些在7天內(nèi)玩過(guò)游戲的玩家,我們收集了自從每個(gè)游戲發(fā)布以來(lái)他們第一次訪(fǎng)問(wèn)該網(wǎng)站的信息,以及他們?cè)诘谝淮卧L(fǎng)問(wèn)后的5天內(nèi)是否玩了表1中的每個(gè)游戲。然后,我們收集了他們的Kongregate朋友玩游戲的數(shù)據(jù)。</p><p><b>  3.總結(jié)和結(jié)論</b></p><p>  在這項(xiàng)研究中,我們檢查了玩家的Kongregate朋友的數(shù)量對(duì)玩家選擇游戲的可能性的影

71、響。除了玩家的較早玩游戲的Kongregate朋友的數(shù)量的影響之外,我們還思考了玩家與較早玩游戲的Kongregate朋友之間的聯(lián)系強(qiáng)度是否對(duì)玩家選擇游戲的可能性的產(chǎn)生影響。</p><p>  我們發(fā)現(xiàn),較早玩游戲的Kongregate朋友的數(shù)量對(duì)玩家選擇游戲的影響是積極的,但是較早玩游戲的Kongregate朋友是否與玩家有聯(lián)系強(qiáng)度,并無(wú)統(tǒng)計(jì)學(xué)意義。這一發(fā)現(xiàn)表明,人際影響對(duì)產(chǎn)品選擇的重要性的一些理論如創(chuàng)新擴(kuò)散

72、理論(羅杰斯,2003)和計(jì)劃行為理論(阿杰恩,1991),在網(wǎng)絡(luò)休閑游戲環(huán)境中并不十分適用。</p><p>  在這項(xiàng)研究中,我們只考慮了較早玩游戲的Kongregate朋友的數(shù)量對(duì)玩家選擇游戲的影響。然而,如其他研究(例如,烏干達(dá)等人,2012)中發(fā)現(xiàn)的,由較早玩游戲的Kongregate朋友組成的玩家個(gè)人網(wǎng)絡(luò)的其他特征,例如群集數(shù)量,比起玩家朋友的數(shù)量,其產(chǎn)生的影響可能更大。因此,在未來(lái)的研究中,應(yīng)該檢查

73、玩家個(gè)人網(wǎng)絡(luò)的其他特征,而不是朋友的數(shù)量。我們還發(fā)現(xiàn),其他因素,如類(lèi)型偏好、玩家在游戲發(fā)布后首次訪(fǎng)問(wèn)該網(wǎng)站的時(shí)間、游戲的獨(dú)特特征在預(yù)測(cè)玩家的選擇游戲方面發(fā)揮了重要作用。</p><p>  這項(xiàng)研究有一定的局限性。首先,在這項(xiàng)研究中所考察的游戲的類(lèi)型是智商測(cè)試和拼圖。Kongcompate朋友對(duì)玩家選擇游戲的影響有可能因游戲的類(lèi)型而異。其次,本次研究中的兩場(chǎng)游戲都是單人游戲。Kongregate朋友對(duì)玩家選擇這兩

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