会展经济与管理新媒体营销中英文对照外文翻译文献

中英文对照外文翻译(文档含英文原文和中文翻译)原文:Social Networks and the Mass MediaAdapted 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 network 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 individual’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 offered 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 accountability through existing frie nd relationships. There are a number of advantages gained by leveraging 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 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 incorporates 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 RThough 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 allthree 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 mediaIn 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 1992).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 politician, 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.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。