1、1会展经济与管理新媒体营销中英文对照外文翻译文献导读：就爱阅读网友为您分享以下“会展经济与管理新媒体营销中英文对照外文翻译文献”资讯，希望对您有所帮助，感谢您对 的支持!中英文外文翻译(文档含英文原文和中文翻译)原文: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
2、 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 itiesFacebook enables individuals to encourage oth
3、ers to joint he netwo2rk 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,
4、 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 n
5、ow 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 users Facebook credenti
6、als 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 ap
7、proach to application development. By tappin g into an already established 3community around a particular social netw orking platform, it becomes unnecessary to require users to register wit h another system.4The structure of a Social Network is essentially the formation of a dynamic virtual communi
8、ty 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 creatio
9、n 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 participati
10、on 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
11、 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 5an object that is being discussed focusing on both cognitive (based on utilitarian motive concerning an individua ls concern wi
12、th the cost and benefit of the product or service) and aff ective (a value-expressive motive, referring to an individuals 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).6It is also useful to und
13、erstand, 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 shor
14、t 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. Computati
15、on 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.
16、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 c
17、omputing model in which virtualized 7resources 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).
18、 In both cases guarantees are offere8d through customized Service 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 accountabili
19、ty through existing frie nd relationships. There are a number of 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 through existing us
20、er 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
21、, 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
22、9Batten 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 i10ncorporates
23、 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,
24、 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
25、.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.
26、 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 medias impact. For example, ad
27、ditional weak ties between disparate social 11groups can reduce the medias impact, an d the presence of unified social elites can eliminate the medias impact entirely in the aggregate. Empirical studies of media impact that fail t o consider medias interaction with social networks risk bias.12Second
28、, 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 posi
29、tive 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, t
30、ends 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
31、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 13theory incorporates empirically realistic het
32、erogeneity acr oss people in all three factors.14Additionally, people are exposed to individuals, groups, and organiz ations external to ones network, such as mass media outlets, state prop aganda, national party leaders, NGOs, and Internet personalities. These outlets can provide information, incre
33、asing 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 person
34、al 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. A
35、s before, many goals could u nderlie advocacy beyond just the support of a biased media outlets 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
36、 in which one of the two options is the status quo, and all individuals begin supporti ng it. For political participation and social 15movements, 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 incumben
37、t polit16ician, 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 conte
38、xts 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 outle
39、ts with the addition of parameters dictating th eir relative strengths.17二、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
40、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
41、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18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19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
42、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”
43、。 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20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21义上，这个模型是类似于一个志
44、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，
45、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；它是一22个“消息”模型（扎勒 1992） 。23我把我的分析集中在三个部分
46、，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。24谢谢下载！25百度搜索“就爱阅读”,专业资料,生活学习,尽在就爱阅读网,您的在线图书馆
