Blog network structure

squashed · Blog network structure

tool to chart network

http://goosebumps4all.ifastnet.com/34all/gallery.html

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http://www.mvblogs.org/visuals/visual.php

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Vizualisation tools

http://processing.org/

via
http://infosthetics.com/archives/...s_data_visualization_network.html

see also

http://playground.audioscrobbler.com/martind/chart_arcs/

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The Psychology of Failure
When you look at groups that hit a failure cascade, you notice patterns. If you were to chart an alliance's membership over time, once you reach the failure cascade, you'd see a downward-sloping curve with a dispersal of cliffs. These are the two forces at work in that alliance's failure cascade: the individual and the guild. Individuals leaving the alliance cause the shape of the slope, and the cliffs signify the points at which an entire guild has left an alliance.

This happens because the failure cascade is the inverse of a network effect. Websites like MySpace define their value by the people that use the service just as guilds define their quality by their members. As bad events cause players to leave or become inactive, the quality drop leads others to do the same in a spiral that rarely stabilizes, until no one is left.

To an individual, a failure cascade brings with it a change in that person's identity. Instead of saying he is a member of an alliance, he shifts his perspective locally, to his guild or himself. These changes can fracture an alliance and set the stage for its member guilds to fight among themselves.

http://www.escapistmagazine.com/a...4/2645-Riding-the-Failure-Cascade

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Node ID Assignment

Cubit nodes are distributed in the same space as keywords. Each node in Cubit is assigned a unique string ID chosen from the set of keywords associated with previously inserted objects in the system. Specifically, at join time each node independently selects a random keyword, ensuring uniqueness by detecting ID collisions. The ID of a node determines its "position" in the keyword space. This position determines how a given node is used in Cubit. First, each Cubit node is responsible for storing the set of keywords for which it is the closest node. Second, Cubit implements a distributed protocol which navigates through nodes in the keyword space, gradually zooming in on a neighborhood of a given (possibly misspelled) keyword, and thus locates nodes that store possible matches.
Navigation

Multi-resolution rings

Figure 2: In this example, the solid circles represent peers in node A's peer-set, the empty circles represent other peers, and the squares represent object keywords in the system. The shaded region depicts the sub-space that is closer to A than any other node.
The navigation protocol is the core component of Cubit. To support this protocol, Cubit creates and maintains a multi-resolution overlay network on nodes such that each node has several peers at every distance from itself; the peers at a given distance are chosen to maximize the coverage of that region. This is illustrated in Figure 2. Such overlay design is inspired by the small-world construction in which a grid is augmented by a sparse set of randomly chosen edges, with roughly the same number of edges for each distance scale. In the resulting graph a simple greedy routing algorithm (which on each step minimizes the distance to target) succeeds in finding short routes to any given target.

The desired property of the search protocol is to obtain the k closest objects to the set of keywords, as measured by the phrase distance metric. For each keyword in the search phrase, the protocol obtains the k closest objects from each node which meets the following edit distance criterion: its ID is within an edit-distance of q from the keyword, where q is the product of the keyword length and the expected number of perturbations per character (which is a parameter in the system). The protocol selects m closest nodes if fewer than m nodes meet edit-distance criterion, where m is called the search fan-out. The keyword search protocol is illustrated in Figure 3.

http://www.cs.cornell.edu/~bwong/cubit/approach.html