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Items in bibliography identified by a string matching small world

Ackerman03
.Open Ackerman03
 Jody Ackerman
 Uniting with only a few random links
 Newswise
.See http://www.newswise.com/articles/view/?id=RANDOM.RPI
 =ARTICLE NONSEQUENTIAL NET PARALLEL COMPUTATION
 Use a small world network to keep processes synchronized with minimal overhead.
 Regular communication with a few neighbors + a few connections with random distant processes.
 Research by Korniss at Rensslaer (RPI)
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AdamicHuberman01
.Open AdamicHuberman01
 Lada A Adamic & Bernardo A Huberman
 The Web's Hidden Order
 Commun ACM V44n9(Sep 2001)pp55-59
 =ANALYSIS NET/WEB WWW COMPLEXITY SMALL-WORLD POWER-LAW DYNAMIC MODEL ECONOMICS
 power_law(\beta) ::= Net{ for some constant c, frequency = c /(size**\beta). }.
 WWW shows exponential growth.
 number of pages per site, number of users, number of outlinks, and number of inlinks all have close to a 1/n**2 distribution.
 This can be accounted for by two random growth models. stochastic rate of growth proportional to size.  Either starting at different times, or with different growth rates.
  Usage is an 80-20 phenomenon.
  Implication: any site gets a few visitors each day, few get large numbers...
 winner take all markets.
 small worlds effect because some sites have lots of links.  diameter between sites is about 4 clicks. between pages about18 clicks.
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Denning04c
.Open Denning04c
 Peter J Denning
 Network Laws
 Commun ACM V47n11(Nov 2004)pp15-20 
 =SURVEY MATHEMATICS NETWORKS  RANDOM GRAPHS POWER LAWS SMALL WORLDS
 Clique: highly connected subset with few connections outside the clique.
 Hubs: nodes with many links.
 Broker: the only connection between a pair of cliques.
 Bridge: connected to several cliques In many real networks the Pr[k links at a node] = (1/k)**p, "power law".
 Accounted for by new nodes being created at random and connecting to nodes wit
h larger numbers of links.
 Hubs are key for  securing and using a network.
 Command a network by communicating intent  and delegating decision making.
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Kleinberg08
.Open Kleinberg08
 Jon Kleinberg 
 The Convergence of Social and Technological networks 
 Commun ACM V51n11(Nov 2008)pp66-72
.See http://doi.acm.org/10.1145/1400214.1400232
 =EMPIRICAL 6DEGREES SMALL WORLDS GRAPHS WEB/NET Milgram  SOCIOLOGY CONTAGION MIMETICS IDEAS
 Evidence that real social networks are "small worlds" as predicted.
 Evidence that ideas spread in jagged trees through the network.
 "Contagion as a Design Priciple" 
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NewmanBarabasiWatts06
.Open NewmanBarabasiWatts06
 Mark Newman & Albert Barabasi & Duncan J Watts 
 The Structure and Dynamics of Networks 
 Princeton UP Princeton NJ 2006 ISBN 0691113572 $CR 0810-0946
  =UNREAD =SURVEY RANDOM GRAPH THEORY SMALL WORLDS NET COMPLEXITY 
 Notes
.Hole 
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Shirky03
.Open Shirky03
 Clay Shirky 
 A Group Is Its Own Worst Enemy 
 ETech (Apr 2003 ) + Published July 1, 2003 on the "Networks, Economics, and Culture" mailing list.
.See http://shirky.com/writings/group_enemy.html
 =TALK =HISTORY WWW/NET SOCIAL GROUP PEOPLE CULTURE WEB2.0  TEAM  
 Refers to W.R. Bion: "Experiences in Groups": 
Groups of people become both collections of individuals and a self-coordinating  entitiy.
Therapeutic groups tend to: talk sex, identify external enemies, and religiously venerate something.
Need for structure for groups to work.
In particular rules for creating rules...
 Examples of BBSs, Usenet, .... where open free group is invaded.
 Therefore need structure in social systems.
 Technology (TCP/IP, WiFi, IM, Mobile phones, ...) now lets all people be online together.
 Example. Ito's Conference call moderated on chat with wiki for references.
 For a given technology -- most groups fail!
 Accept:
.List
 Social and technical issues are intertwingled: they can not be separated niether does the technical drive the social. 
The system will have antics -- emergent properties.
There will be a formal rules and informal rules.
 Members are not just users. 
There will be an onion structure. 
Example: reader -> anonamous coward  -> named person  -> moderator.
The Core subgroup love and weed the garden that others wander through (and vandalize?).  = Volunteer fire department.
 `One user = one vote` does not work when anybody can be a user.
.Close.List
 Things to design for
.List
 Give members a handle -- stable local name.  So they get a reputation.
 Make a simple way for behavior to be visible --  who is in good standing?
 Make it difficult to enter the core subgroups.
The `group` is the real user!
 Make the communications scale.  
Encourage a `small world` structure. Many linked small groups.
.Close.List
 Compare the experience in
.See  [Wolf09]
of Craig's List.
 Also see
.See [Shirky08]
for the social impact of free communication and publishing.
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Shirky08
.Open Shirky08
 Clay Shirky 
 Here comes everybody
 Penguin NY NY 2008 HM851 S5465 ISBN 978-1-59420-153-0
 =EXAMPLES SOCIOLOGY WEB/NET ECONOMICS SOCIAL CAPITAL SMALL WORLDS POWER LAWS
 Net lowers cost of communication, publication, copying, collaboration  to ZERO.  So a lot more of all of these.
 More is Different.  Faster is Different.
 New paradigm: Publish; Filter.
 Many attempts, failure is free, on the way to one big success.
 A shared resource needs motivated people and people need Face-to-face meetings.
 Developing_a_resource::= Promise; Tool; Bargain.
 Examples: Usenet FlashMobs F/OSS Linux SourceForge Flickr MySpace FaceBook MeetMe EBay Wikipedia Wikitorial Encarta
 Also see short article
.See [Shirky03]
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Watts99
.Open Watts99
 Duncan J Watts
 Small worlds: the dynamics of networks between order and randomness
 Princeton Univ Press NJ 1999 ISBN 0-691-00541-9 CR9911-0823
 =ESSAY ADVERT THESIS math complexity graph communications
 Examines path lengths in ordered, random, and inbetween graphs.
 Kevin Bacon Graphs.
 Games on graphs. 
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