網(wǎng)絡新聞傳播概論

溫馨提示：本課程作業(yè)無需在學習平臺上提交，請獨立完成后提交給學習中心，由學習中心上報課程成績。

一、名詞解釋（共3題，每題10分）

1、網(wǎng)絡中立（Net Neutrality）

2、意見領(lǐng)袖 (opinion leader)

3、賽博格（cuborg）

二、簡答題（共2題，每題35分）

1、請介紹算法推送在新聞行業(yè)運用的現(xiàn)狀，并分析這一新技術(shù)是否會帶來“信息繭房”。（600字以內(nèi)）

2、數(shù)字化社會研究領(lǐng)域具有影響力的學者范戴克（José van Dijck）提出“平臺社會”（platform society）的概念來理解我們當下所處的信息環(huán)境。請閱讀以下節(jié)選段落，并選擇某一個角度、結(jié)合自己的生活經(jīng)歷，歸納和闡述你對“平臺社會”的理解。

In the introduction, we defined a platform as a programmable architecture designed to organize interactions between users. Many people think of platforms simply as technological tools that allow them to do things online: chatting, sharing, commenting, dating, searching, buying stuff, listening to music, watching videos, hailing a cab, and so on. But these online activities hide a system whose logic and logistics are about more than facilitating: they actually shape the way we live and how society is organized (Gehl 2011). Now let us first look more closely at the elements that construct a single platform’s anatomy: a platform is fueled by data, automated and organized through algorithms and interfaces, formalized through ownership relations driven by business models, and governed through user agreements. We will zoom in on each of these technical, economic, and sociolegal elements to explain the nature of their governance power, before we explore their mechanisms and effects in the next chapter.

Platforms automatically collect large amounts of data— both content data and user data (Driscoll 2012; Mayer- Sch?nberger and Cukier 2013; Turow 2012; Van Dijck, 2014). The collection of data is enabled and shaped by hardware and software; devices people use to access platform services often come equipped with software and apps that can automatically collect data. With each mouse click and cursor movement user data are generated, stored, automatically analyzed, and processed— not just Internet protocol addresses and geolocations but detailed information about interests, preferences, and tastes. Large quantities of data are also collected across the Web through the implementation of “social buttons” and “pixels” (Facebook, Twitter, LinkedIn, Instagram, YouTube, or Google+) on websites (Gerlitz and Helmond 2013).

Data provide the fuel for a growing connectivity between platforms. By means of application programming interfaces (APIs), platforms, subsequently, offer third parties controlled access to their platform data, giving them detailed insights into user behavior and metrics— information on which they can build new applications or platforms (Helmond 2015; Langlois et al. 2009; Zittrain 2008).5 Since eBay launched the first open API in the year 2000, its ubiquitous employment has arguably transformed the Web into a data- driven, platform- based ecosystem.

Algorithms are another significant technological ingredient defining the connective architecture of platforms; they are sets of automated instructions to transform input data into a desired output (Gillespie 2014; Pasquale 2015). For instance, Google’s PageRank algorithms define the relevance of a web page by calculating the number and quality of hyperlinks to this page. And Facebook’s News Feed algorithms determine the content you will be exposed to, calculated on the basis of the online activities of “friends” and “friends of friends” (Bucher 2012). Platforms use algorithms to automatically filter enormous amounts of content and connect users to content, services, and advertisements. Although platform owners may lift a veil on how their algorithms work, they are often well- kept trade secrets and are everything but transparent.

Moreover, algorithms have become increasingly complex and are subject to constant tweaking. Shifting the focus from technological to economic relations, two particularly important ingredients of a platform’s architecture are its ownership status and business model. To start with the former, each platform has a specific legal– economic status; most distinctively, platforms may be operated on a for- profit or a nonprofit basis, even though such labels often leave implicit who stands to profit from a platform’s activities.7 Airbnb, for instance, is run by a US company with headquarters in San Francisco and satellite offices in nineteen cities around the world; the company is owned by its stockholders, who are, besides its founders, a number of Silicon Valley venture capitalists. Whether a company calls itself “global” or “American” has implications for compliance with regulatory regimes including taxation.

Ownership status also has consequences for a site’s economic transactions and its social interactions with users. It is relevant for users to recognize owner– consumer relationships, especially because they may change over time. Couchsurfing Inc. is a case in point; the “hospitality site” started in 2005 as the Couchsurfing Collectives, with local teams operating from the United States, Canada, Austria, and New Zealand. When the site changed from a volunteer- based organization financed by donations to a corporation in 2011, many members objected to the shift from a nonprofit “travelers network” to a for- profit “accommodation site.” The switch translated accordingly into the selection of a different business model. Business models in the context of platforms refer to the ways in which economic value gets created and captured. In the online world, value gets measured in various types of currency: along with money and attention, data and user valuation have become popular means of monetization.9 One of the most pertinent myths is that platform services are “free” because many do not charge for their services. Facebook, Twitter, and Google+ are just a few of the many online social networks that are monetized through automating connections between users, content, data, and advertising (Couldry 2015; Fuchs 2011; Turow 2012). The “free” strategies adopted by many platforms have resulted in an ecosystem where the default mode is to trade convenient services for personal information (Schneier 2015).

Technological and economic elements of platforms steer user interaction but simultaneously shape social norms. Although a platform’s architecture affords a particular usage and users are often met with a finite set of possible options, they are not “puppets” of the techno- commercial dynamics inscribed in a platform. Through its interfaces, algorithms, and protocols, a platform stages user interactions, encouraging some and discouraging other connections (Helmond 2015); for example, inserting a “l(fā)ike button” in the right- hand corner of an interface activates more “l(fā)iking” than an insertion in the left- hand corner. Indeed, one could argue that any major platform is a recalibration laboratory where new features are constantly tested on users (Benbunan- Fich 2016).

Another important element in platform- governing methods is its user agreement, usually called “terms of service” (ToS). These pseudo- legal contracts define and shape the relationships between users and platform owners, but they are often long, difficult to understand, and subject to constant change, which is why many people check the box without even looking at this “agreement.”

以上內(nèi)容節(jié)選自Van Dijck, J., Poell, T., & De Waal, M. (2018). The platform society: Public values in a connective world. Oxford University Press.

奧鵬，國開，廣開，電大在線，各省平臺，新疆一體化等平臺學習
詳情請咨詢QQ : 3230981406或微信:aopopenfd777