Zizi Papacharissi-A Networked Self_ Identity, Community, and Culture on Social Network Sites-Routledge英文书籍资料.pdf
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1、 A Networked SelfA Networked Self examines self presentation and social connection in the digital age. This collection brings together new theory and research on online social networks by leading scholars from a variety of disciplines. Topics addressed include self presentation, behavioral norms, pa
2、tterns and routines, social impact, privacy, class/gender/race divides, taste cultures online, uses of social networking sites within organizations, activism, civic engagement and political impact.Zizi Papacharissi is Professor and Head of the Communication Department at the University of Illinois-C
3、hicago. She is author of A Private Sphere: Democracy in the Digital Age and editor of Journalism and Citizenship: New Agendas, also published by Routledge.A Networked SelfIdentity, Community, and Culture on Social Network SitesEdited by Zizi PapacharissiFirst published 2011 by Routledge 270 Madison
4、Avenue, New York, NY 10016Simultaneously published in the UK by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RNRoutledge is an imprint of the Taylor these hubs hold the whole network together. The difference between these two types of networks is the existence of these hubs. The hubs f
5、unda- mentally change the way the network looks and behaves. These differences become more evident when we think about travel from the east coast to west coast. If you go on the highway system, you need to travel through many major cities. When you fly, you fly to Chicago and from Chicago you can re
6、ach just about any other major airport in the U.S. The way you navigate an airline network is fundamentally different from the way you navigate the highway system, and its because of the hubs.So we saw that the Web happens to be like the airline system. The hubs are obviousGoogle, Yahoo, and other w
7、ebsites everybody knowsand the small nodes are our own personal Web pages. So the Web happens to be this funny animal dominated by hubs, what we call a “scale- free network.” When I say “scale- free network,” all I mean is that the network has a power law distri- bution; for all practical purposes y
8、ou can visualize a network as dominated by a few hubs. So we asked, is the structure of the Web unique, or are there other networks that have similar properties?Take for example the map of the Internet. Despite the fact that in many peoples minds the Internet and Web are used interchangeably, the In
9、ternet is very different from the Web because it is a physical network. On the Web, it doesnt cost any more money to connect with somebody who is next door than it does to connect to China. But with the Internet, placing a cable between here and China is quite an expensive proposition.On the Interne
10、t the nodes correspond to routers and the links correspond to physical cables. Yet, if one inspects any map of the Internet, we see a couple of major hubs that hold together many, many small nodes. These hubs are huge routers. Actually, the biggest hub in the United States is in the Midwest, in a we
11、ll- guarded underground facility. Well see why in a moment. Thus, like the Web, the Internet is also a hub- dominated structure. I want to empha-Introduction and Keynote to A Networked Self 5size that the Web and the Internet are very different animals. Yet, when you look at their underlying structu
12、res, and particularly if you mathematically analyze them, you will find that they are both scale- free networks.Lets take another example. Im sure everybody here is familiar with the Kevin Bacon game, where the goal is to connect an actor to Kevin Bacon. Actors are connected if they appeared in a mo
13、vie together. So Tom Cruise has a Kevin Bacon number one because they appeared together in A Few Good Men. Mike Myers never appeared with Kevin Baconbut he appeared with Robert Wagner in The Spy Who Shagged Me, and Robert Wagner appeared with Kevin Bacon in Wild Things. So hes two links away. Even h
14、istorical figures like Charlie Chaplin or Marilyn Monroe are connected by two to three links to Bacon. There is a network behind Hollywood, and you can analyze the histor- ical data from all the movies ever made from 1890 to today to study its struc- ture. Once again, if you do that, you will find e
15、xactly the same power law distribution as we saw earlier. Most actors have only a few links to other actors but there are a few major hubs that hold the whole network together. You may not know the names of the actors with few links because you walked out of the movie theater before their name came
16、up on the screen. On the other hand there are the hubs, the actors you go to the movie theater to see. Their names are on the ads and feature prominently on the posters.Lets move to the subject of this conference, online communities. Here, the nodes are the members. And though we dont know who they
17、are, their friends do, and these relationships with friends are the links. There are many ways to look at these relationships. One early study from 2002 examined email traffic in a university environment, and sure enough, a scale- free network emerged there as well. Another studied a pre- cursor to
18、Facebook, a social networking site in Sweden, and exactly the same kind of distribution arose there. No matter what measure they looked at, whether people just poked each other, traded email, or had a relationship, the same picture emerged: most people had only few links and a few had a large number
19、.But all the examples I have given you so far came from human- made systems, which may suggest that the scale- free property is rooted in something we do. We built the Internet, the Web, we do social networking, we do email. So perhaps these hubs emerge as something intrinsic in human behav- ior. Is
20、 it so?Lets talk about whats inside us. One of the many components in humans is genes, and the role of the genes is to generate proteins. Much of the dirty work in our cells is done not by the genes, but by the proteins. And proteins almost never work alone. They always interact with one another in
21、what is known as proteinprotein interaction. For example, if you look in your blood stream, oxygen is carried by hemoglobin. Hemoglobin essentially is a molecule 6 Introduction and Keynote to A Networked Selfmade of four proteins that attach together and carry oxygen. The proteins are nodes in a pro
22、teinprotein interaction network, which is crucial to how the cell actually works. When its down, it brings on disease. Theres also a meta- bolic network inside us, which takes the food that you eat and breaks it down into the components that the cells can consume. Its a network of chemical reactions
23、. So the point is that there are many networks in our cells. On the left- hand side of this figure is the metabolic network of the simple yeast organ- ism. On the right- hand side is the proteinprotein interaction network. In both cases, if you analyze them mathematically you will observe a scale- f
24、ree network; visually you can see the hubs very clearly.Figure I.2 Protein interaction network of yeast, an organism often studied in biologi- cal labs. Each node corresponds to a protein and two proteins are linked together if there is experimental evidence that they interact with each other in the
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