Small-world network Small-world network exampleHubs are bigger than other nodes Average vertex degree = 1,917 Average shortest path length = 1.803. Clusterization coefficient = 0.522 Random graph Average vertex degree = 1,417 Average shortest path length = 2.109. In the context of a social network, this results in the small world phenomenon of strangers being linked by a mutual acquaintance. Properties of small-world networks[edit] This property is often analyzed by considering the fraction of nodes in the network that have a particular number of connections going into them (the degree distribution of the network). ) is defined as R. Examples of small-world networks[edit] Small-world properties are found in many real-world phenomena, including road maps, food chains, electric power grids, metabolite processing networks, networks of brain neurons, voter networks, telephone call graphs, and social influence networks. Examples of non-small-world networks[edit] Network robustness[edit] See also[edit] References[edit]
BookBuzzr-Free Online Book Marketing Technology for Authors IT Conversations: Noshir Contractor Recent technological advances in hardware and software, broadband connectivity, and the decreasing cost of computers, cell phones, and other such devices have created an environment where we can connect with anyone, anytime, anywhere almost effortlessly. However, how do we determine with whom we want to connect? The answers to this question can be found by studying the underlying socio-technological motivations for the creation, maintenance, destruction, and reconstitution of knowledge and social networks. Dr. Dr. IT Conversations' publication of this program is underwritten by your donations and: Dr. He is the author of over 250 research papers in communication. Dr. Resources: This presentation is one of a series from the MeshForum 2005 Event held in Chicago, Il, May 1-4, 2005. For Team ITC: Description editor: Chase SouthardPost-production audio engineer: Stuart HunterSeries Editor: Cori Schlegel
In networks, cooperation trumps collaboration In networks, cooperation trumps collaboration. Collaboration happens around some kind of plan or structure, while cooperation presumes the freedom of individuals to join and participate. Cooperation is a driver of creativity. Stephen Downes commented here on the differences: collaboration means ‘working together’. That’s why you see it in market economies. markets are based on quantity and mass.cooperation means ’sharing’. We are only beginning to realize how we can use networks as our primary form of living and working. Wirearchy: a dynamic multi-way flow of power and authority based on information, knowledge, trust and credibility, enabled by interconnected people and technology. Heterarchies are networks of elements in which each element shares the same “horizontal” position of power and authority, each playing a theoretically equal role [wikipedia]. Chaordic refers to a system of governance that blends characteristics of chaos and order. You cannot train people to be social.
Scale-free network A scale-free network is a network whose degree distribution follows a power law, at least asymptotically. That is, the fraction P(k) of nodes in the network having k connections to other nodes goes for large values of k as where is a parameter whose value is typically in the range 2 < < 3, although occasionally it may lie outside these bounds.[1][2] History[edit] In studies of the networks of citations between scientific papers, Derek de Solla Price showed in 1965 that the number of links to papers—i.e., the number of citations they receive—had a heavy-tailed distribution following a Pareto distribution or power law, and thus that the citation network is scale-free. Barabási and Albert proposed a generative mechanism to explain the appearance of power-law distributions, which they called "preferential attachment" and which is essentially the same as that proposed by Price. (that is, the number of edges incident to ) by . Characteristics[edit] Random network (a) and scale-free network (b).
TGIF Book Marketing Tips: Everything You Do Online Reflects on Your Book Everything You Do Online Reflects on Your Book: Make Sure That Reflection Is Professional Guest Expert: Phyllis Zimbler Miller This month’s guest post is a natural extension of last month’s guest post “Do Your Offline and Online Book Promotion Activities Support Each Other?” In that post I talked about how your book author website should present consistent information about your offline and online book promotion activities. In addition, all your online book promotion activities should present you as a professional book author, regardless of whether your book was traditionally published or self-published. Recently a book marketing consulting client asked me why he could not build a website himself for his nonfiction book the same as he had built for his business. When he said yes, I told him that his business site did not look professional. And this advice about professionalism extends to everything you do online to promote your book. Why is this so important? 0stumbleupon
&G/localization: When Global Information a danah boyd O'Reilly Emerging Technology Conference March 6, 2006"G/localization: When Global Information and Local Interaction Collide" [This is a rough crib of the actual talk.] Citation: boyd, danah. 2006. "G/localization: When Global Information and Local Interaction Collide." O'Reilly Emerging Technology Conference, San Diego, CA. Good afternoon. My talk today is about "glocalization," one of the most grotesque words that academics have managed to coin. Glocalization is the ugliness that ensues when the global and local are shoved uncomfortably into the same concept. I want to talk about what it means to connect the global and local together in technology and how this affects the design process. The digital era has allowed us to cross space and time, engage with people in a far-off time zone as though they were just next door, do business with people around the world, and develop information systems that potentially network us all closer and closer every day.
Progressive Strategy Blog Random graph Random graph models[edit] A random graph is obtained by starting with a set of n isolated vertices and adding successive edges between them at random. The aim of the study in this field is to determine at what stage a particular property of the graph is likely to arise.[2] Different random graph models produce different probability distributions on graphs. Most commonly studied is the one proposed by Edgar Gilbert, denoted G(n,p), in which every possible edge occurs independently with probability 0 < p < 1. .[3] A closely related model, the Erdős–Rényi model denoted G(n,M), assigns equal probability to all graphs with exactly M edges. with 0 ≤ M ≤ N, G(n,p) has elements and every element occurs with probability .[2] The latter model can be viewed as a snapshot at a particular time (M) of the random graph process , which is a stochastic process that starts with n vertices and no edges, and at each step adds one new edge chosen uniformly from the set of missing edges. that a given edge .
Snap-together Sphere by aubenc A simple sphere made from three interlocked rings I made one day to show the whole process to a friend. The dimensions of the rings in the provided stl files are 60mm outer diameter, 20mm height and 3mm thickness. They have been generated with one face at every 2mm of the perimeter and also, a gap of 0.4mm in the slots which gave a nice fit for the rings printed by bot1334. The zip file contains two more examples (40mm diameter, 5mm and 10mm height and, if I'm not wrong, 2mm thickness) however, I was not using any "gap" parameter for those so... they'll need some cleaning to fit properly. Some more pics: UPDATE: Replaced the OpenSCAD file with v3 version which fixes a bug in the tolerances between rings.
The Social Networking Faceoff Written by Alex Iskold and edited by Richard MacManus. With all this buzz around the potential Yahoo! acqusition of Facebook for $1Billion, we think it's time to do the social networking faceoff. Arguably of all services in the new social era, the social network sites hold most promise. Another natural trend that we are seeing in the space is demographic segmentation. In addition to those three, Bebo is making some major waves and has surpassed MySpace in UK and New Zealand. The Social Network Faceoff Chart (*) The active user estimate is based on the assumption that MySpace has 70M users. Traffic Dynamics We can gain additional insights by looking at the traffic dynamics over the past year. Orkut is rising? From the charts we clearly see that Orkut is gaining, but why? But perhaps it is not just that Brazilian users dominate, but also the attitude and confidence of Orkut. Conclusion MySpace is an undisputed leader on all counts, but Orkut is on the rise and it's moving very rapidly.
Do It Like a Librarian: Ranganathan for Content Strategists Before becoming a content strategist, I worked as an academic librarian for five years. Although academia and consulting can sometimes seem like different planets, content strategists and librarians have a lot in common—after all, we all love content. Selecting it. S.R. Like content strategists, librarians enjoy a good credo. With a few simple adaptations, Ranganathan’s laws serve as good reminders for content strategists, too. Content is for useLibrarians love a hard-luck case. Image courtesy of University of Wisconsin–Milwaukee LibrariesEvery content its user ANDSave the time of the userThe third law, every content its user, encourages us to act as modern day matchmakers between information and users. So go on.
Average path length Concept[edit] The average path length distinguishes an easily negotiable network from one, which is complicated and inefficient, with a shorter average path length being more desirable. However, the average path length is simply what the path length will most likely be. Definition[edit] with the set of vertices . , where denote the shortest distance between and . if cannot be reached from . is: is the number of vertices in Applications[edit] In a real network like the World Wide Web, a short average path length facilitates the quick transfer of information and reduces costs. Most real networks have a very short average path length leading to the concept of a small world where everyone is connected to everyone else through a very short path. As a result, most models of real networks are created with this condition in mind. The average path length depends on the system size but does not change drastically with it. References[edit]