社交网络和大众传媒中英文对照外文翻译文献

中英文对照翻译
(文档含英文原文和中文翻译)
Social Networks and the Mass Media
Adapted from: American Political Science Review,2013,107 Social networking has become an every day part of many peoples’lives as evidenced by the huge user communities that are part of such networks. Facebook, for instance, was launched in February 2004 by Harvard under graduate students as an alternative to the traditional stud ent directory. In tended to cover interaction between students at Univers ities–Facebook enables individuals to encourage others to joint he netwo
rk through personalized invitations, friend suggestions and creation of s pecialist groups. Today Facebook has a much wider take up than just s tudents at Universities. Facebook now facilitates interaction between peo ple by enabling sharing of common interests, videos, photos, etc. Sharin g,
Some social network populations exceed that of large countries, for example Facebook has over 350 million active users. Social networks provide a platform to facilitate communication and sharing between user s, in an attempt to model real world relationships. Social networking ha s now also extended beyond communication between friends; for instanc e, there are a multitude of integrated applications that are now made a vailable by companies, and some organizations use such applications, su ch as Facebook Connect to authenticate users, i.e. they utilize a user’s Facebook credentials rather than requiring their own credentials(for exa mple the Calgary Airport authority in Canada uses Facebook Connect t o grant access to their WiFi network). This ability to combine a third party application (including its local data) to authenticate users demonstr ates the service-oriented approach to application development. By tappin g into an already established community around a particular social netw orking platform, it becomes unnecessary to require users to register wit h another system.
The structure of a Social Network is essentially the formation of a dynamic virtual community with inherent trust relationships between fri ends. (Szmigin et al., 2006) identify how “relationship marketing” (ident ified as referring to all marketing activities directed towards establishing, developing and maintaining successful relational exchanges) can be faci litated through the creation of on-line communities. They discuss how o n-line communities can be used to facilitate interaction and bonding bet ween consumer and suppliers, intermediate parties and specific brands. Similarly, (Shang et al., 2006) discuss how brand loyalty can be achiev ed through various types of participation within an on-line community (focusing specifically on the –a virtual communit y of Apple users in Taiwan). They discuss the motivation for individua ls to promote certain products during on-line discussions (active particip ants) and for others to remain as lurkers (passive participants). The stu dy particularly focuses on the incentives for participants to contribute to an on-line community, based on the perception of a user about the de gree of relevance towards an object that is being discussed –focusing on both cognitive (based on utilitarian motive –concerning an individua l’s concern with the cost and benefit of the product or service) and aff ective (a value-expressive motive, referring to an indi vidual’s interest in enhancing self-esteem or self-conception, and in projecting his/her desir ed self-image to the outside world through the product or service).
It is also useful to understand, for instance, how such trust relation ships could be used as a foundation for resource (information, hardware, services) sharing. Cloud environments are typically focused on providin g low level abstractions of computation or storage. Using this approach, a user is able to access (on a short term/rental basis) capacity that is owned by another person or business (generally over a computer networ k). In this way, a user is able to outsource their computing requirement s to an external provider –limiting their exposure to cost associated wi th systems management and energy use. Computation and Storage Clou ds are complementary and act as building blocks from which applicatio ns can be constructed –using a technique referred to as “mash-ups”. S torage Clouds are gaining popularity as a way to extend the capabilities of storage-limited devices such as phones and other mobile devices. T here are also a multitude of commercial Cloud providers such as Amaz on EC2/S3, Google App Engine, Microsoft Azure and also many smalle r scale open clouds like Nimbus (Keahey et al., 2005) and Eucalyptus (Nurmi et al., 2009). A Social Cloud (Chard et al., 2010), on the other hand, is a scalable computing model in which virtualized resources co ntributed by users are dynamically provisioned amongst a group of frie nds. Compensation for use is optional as users may wish to share reso urces without payment, and rather utilize a reciprocal credit (or barter) based model (Andrade et al., 2010). In both cases guarantees are offere
d through customized Servic
e Level Agreements (SLAs). In a sense, thi s model is similar to a Volunteer computing approach, in that friends s hare resources amongst each other for little to no gain. However, unlik e Volunteer models there is inherent accountability through existing frie nd relationships. There are a number o
f advantages gained by leveragin
g social networking platforms, in particular one can gain access to hug e user communities, can exploit existing user management functionality, and rely on pre-established trust formed throug
h existing user relations hips.
The author thanks Jason Barabas, Jon Bendor, Ted Carmines, Jami e Druckman, John Freeman, Matt Golder, Sona Golder, Bob Jackson, J enn Jerit, Kris Kanthak, ?zge Kemahlioglu, Charlotte Lee, Valerie Marti nez-Ebers, Adam Meirowitz, Scott McClurg, Will Moore, Chris Reenock, John Ryan, John Scholz, Jake Shapiro, Anand Sokhey, Jeff Staton, Ji m Stimson, Craig Volden, Jon Woon, four very helpful anonymous revi ewers, and audiences in the Political Economics group at the Stanford GSB, Political Science departments at FSU, GWU, Minnesota, Pittsburg h, and Stony Brook, and the Frank Batten School of Leadership and P ublic Policy at UVa. Any errors are my own.
To begin to answer this question, I develop a novel theory of aggr egate opinion and behavior. The theory considers a heterogeneous popul ation of individuals who must choose between dichotomous options. It i
ncorporates the interaction of social network and mass media influences at the individual level; its key assumption is that the more others cho ose an option, the more one is apt to do so as well. In the theory, soc ial networks provide information about the choices of those to whom o ne is directly connected, while the mass media provide (potentially bias ed) information about aggregate choice. The theory thus applies to, for example, voter turnout and political participation (e.g., Gerber, Green, a nd Larimer 2008; Lake and Huckfeldt 1998; Leighley 1990; McClurg 2 003; Rolfe 2012), opinion formation (e.g., Beck et al. 2002; Druckman and Nelson 2003; Huckfeldt and Sprague 1995), protests and social mo vements (e.g., Kuran 1991; McAdam 1986), and vote choice (e.g., Beck 2002; Huckfeldt and Sprague 1995; Ryan 2011; Sinclair 2012; Sokhey and McClurg 2012).
Three major results follow from this theory. All hold both when in dividuals treat media identically and when they select into media in lin e with their preferences. First, understanding the aggregate effect of the media generally requires considering social networks, because social ne twork structure conditions media's impact. For example, additional weak ties between disparate social groups can reduce the media's impact, an d the presence of unified social elites can eliminate the media's impact entirely in the aggregate. Empirical studies of media impact that fail t o consider media's interaction with social networks risk bias.
Second, social networks can amplify the effect of media bias. A bi ased media outlet that systematically under- or over-reports a poll of th e population by a only a few percentage points can in some cases swi ng aggregate behavior (e.g., turnout or vote share) by over 20% in eith er direction due to positive feedback within the network. Open advocate s in the media can have a yet larger impact even when not comparativ ely influential. Unified social elites limit the effect of media bias, but c annot fully counter an advocate; selection into media, made ever easier with technological improvements, tends to enhance the effect of bias. We should therefore expect media bias to become increasingly importan t to aggregate behavior.
AN INDIVIDUAL-LEVEL THEORY OF AGGREGATE BEHAVIO R
Though I present a theory of aggregate behavior, it is based on in dividual-level assumptions informed by what we know about the way p ersonal characteristics, social networks, and mass media outlets affect in dividual behavior. Due to this, the theory can explore the effect that int eractions between these three factors have on aggregate behavior. As i mportantly, the theory incorporates empirically realistic heterogeneity acr oss people in all
three factors.
Additionally, people are exposed to individuals, groups, and organiz ations external to one's network, such as mass media outlets, state prop aganda, national party leaders, NGOs, and Internet personalities. These outlets can provide information, increasing political knowledge.
As this small sampling of large literatures indicates, individuals' de cisions are influenced by the information they obtain via both local soc ial networks and global media outlets. However, comparatively little sch olarship has explored the three-way interaction of personal characteristic s, social networks, and media
In the second type of bias, which I call advocacy, the media outle t simply states a preference for one of the options, providing no inform ation about aggregate support. The goal in advocacy is to sway the po pulation toward one or the other option. As before, many goals could u nderlie advocacy beyond just the support of a biased media outlet's pre ferences. Advocacy represents the editorial power of the media or the i nfluence of an external actor; it is a "one-message" model (Zaller 199
2).
I focus my analysis in all three sections on the case in which one of the two options is the status quo, and all individuals begin supporti ng it. For political participation and social movements, the status quo is not participating. For opinion formation and vote choice, the status qu o is an existing option such as a policy in place or an incumbent polit
ician, as contrasted with an alternative such as a newly proposed policy or a challenging politician. For simplicity I subsequently call participat ion the option that is not the status quo; this should be read as "partici pation in support of" the option that is not the status quo in contexts o ther than political participation or social movements.
In my analysis I simultaneously vary media strength, network prop erties, media bias, and, for two outlets, the strength of the L outlet. Th ough I keep my analysis to two biased outlets, it can easily be extende d to multiple biased outlets with the addition of parameters dictating th eir relative strengths.
译文:
社交网络和大众传媒
社交网络已经成为许多人每天生活的一部分，即证明了这种网络庞大的用户群体。

例如,由哈佛大学毕业生于2004年2月创作的Facebook 是作为替代传统学生名录的方式存在的。

目的在于覆盖大学-Facebook，使学生个体之间形成互动,鼓励他人通过个性化的邀请、朋友建议和成立专业小组加入网络社交中。

今天的Facebook已变得更加广泛而更不仅仅是在大学生中。

现在，Facebook可以通过共同兴趣,视频,照片的分享来促进人们之间的互动,一些社会网络人数超过一个大国的人数,例如，Facebook有超过3.5亿的活跃用户。

社交网络提供的这个平台能促进用户之间的交流和共享,并试图塑造一个现实世界关系。

当前的社交网络也已不再只是朋友与朋友之间的交流沟通;例如,由公司提供的大量的集成应用程序，现在一些组织正使用这些应用程序,比如Facebook对用户进行身份验证,即他们利用用户的Facebook验证身份,而不需要自己的认证信息(例如加拿大卡尔加里机场当局使用Facebook 验证身份并授予访问无线网络)。

这种联合第三方应用程序的能力(包括其本地数据)对用户进行身份验证说明，服务为导向类似于应用开发。

通过利用已经建立的特定的社交网络平台,要求用户注册另一个系统就变得非常必要了。

社交网络，其结构在本质上是一个通过与固有的朋友之间的信任关系形成的动态的虚拟社区。

斯米登等人于2006确定了如何进行“关系营销”(指所有的营销活动都指向建立、开发和维护一个成功的互相沟通交
流关系)，这可以通过在线社区来实现。

他们讨论如何使用在线社区促进消费者和供应商之间的互动和联系，中间派和特定的品牌。

同样，(商扥人2006)讨论如何通过各种类型的在线社区参与，实现客户对品牌的忠诚度。

（完整译文请到百度文库）他们讨论某些人主动在网上对某些产品进行讨论，促进产品的销售，他们是活跃的参与者，还有一种是在社交网络里担任潜水者，他们是被动参与者。

这方面的研究，会特别关注那些在线社区的参与者，对用户的感知程度的相关性进行讨论——关注彼此的认知和情感。

这对于理解也是非常有用的,例如,如何使这种信任关系成为资源共享的基础 (信息、硬件、服务)。

云环境通常专注于提供低层次抽象的计算或存储。

使用这种方法,用户可以使用(在短期内/租赁的基础上)属于别人或商业(通常在一个计算机网络)的技能。

通过这种方式,用户可以把计算需求外包给外部提供者——限制他们接触系统管理和能源使用中的成本。

计算和云存储是互补的,作为构建应用程序的控制中心——称为“混搭式应用”。

云存储受大众欢迎的原因在于其可以作为一种扩展存储限制的功能设备(如手机和其他移动设备。

大量的商业云提供商如亚马逊 EC2/S3,谷歌应用引擎,微软云和许多规模较小的如雨云(卡舍利et al .,2005)和尤加利(努尔米et al .,2009)。

社交云(查德等人2010)，认为另一方面，是一个由用户动态地非配给一群朋友的可伸缩的虚拟化的计算模型资源。

赔偿是可选的，因为用户可能希望使用共享资源，而不需要没有付款，通过利用基于双方互惠的信贷(或易货)模型(安德拉德等人2010)。

在这两种情况下，可以保证提供定制的服务水平。

在某种意
义上，这个模型是类似于一个志愿者，在朋友之间相互共享资源。

然而，该志愿者模型有固有的责任做好现有的朋友关系。

通过利用社交网络平台获得资源，可以有许多的优势，特别是可以获得巨大的用户群体，可以利用现有的用户管理功能，通过现有的用户依赖形成彼此间的信任关系。

集合行为的individual-level理论
虽然我提出了一个聚合行为理论，它是基于个人层面的假设，我们知道的方式，个人特征，社会网络，和大众媒体影响个人行为的方式。

由于这一理论，该理论可以探索这三个因素之间的相互作用的影响，对聚合行为的影响。

同样重要的是，该理论采用经验现实的异质性，在所有的人三因素。

此外，人们接触到个人，团体和组织外部的网络，如大众媒体的渠道，国家宣传，国家党领袖，非政府组织，和互联网人士。

这些店铺可以提供信息，增加政治知识。

由于这一小样本的大量文献表明，个人的决定是受信息的影响，他们通过当地的社交网络和全球媒体。

然而，相对较少的奖学金，探讨了三方互动的个人特征，社会网络和媒体
在我称之为“宣传”的第二类偏见中，媒体的出口只对一个选项有偏好，不提供信息支持。

宣传的目标是向一个或另一个选择的人口左右摇摆。

正如以前一样，许多目标可以在宣传的基础上进行宣传，不仅仅是支持有偏见的媒体渠道的偏好。

宣传是媒体或外部演员的影响编辑能力；它是一个“消息”模型（扎勒1992）。

我把我的分析集中在三个部分，其中一个选择是现状，所有的人都开始支持它。

对于政治参与和社会运动，现状不参与。

对于民意的形成和投票的选择，现状是一个现有的选择，如一个政策到位或现任的政治家，与另一个替代，如一个新提出的政策或一个具有挑战性的政治家。

为简单起见，我随后致电参与的选项，这是不是现状；这应该是“参与支持”的选项，这是不是在政治参与或社会运动以外的情况下的现状。

结论
虚拟社交网络能促使虚拟社区的形成,其成员有着共同的社会利益并产生社会“价值”。

确定商业模式如何与这样的社会价值相联系一直是许多社交网站主要关注的焦点。

我们这样界定云社交的概念——计算资源(除了简单交流的内容——如消息、照片等等)可以在成员之间进行交换。

然而，事实是被动的，即它是通过在线门户——计算资源而不是其他发布和访问的。

用户参与云社交必须启用访问他们的硬盘数据存储,同时必须信任另一个个体。

我们将讨论如何使用社交网络中的朋友关系作为定义这种关系的基础。

他们还提供了一项关于相关商业模式的调查。

我们相信，这是理解如何使用社交网络在互联网上进行更有效资源共享的第一步。

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