Slashdot Mirror
Detecting Patterns in Complex Social Networks
Roland Piquepaille writes "So-called social networking is very popular these days, as show the proliferation of services like Friendster, Orkut and dozens of others. But do the companies behind these services have any idea of what is hidden inside their complicated networks? When these networks reach a size of millions of users, it's not an easy task. A researcher at the University of Michigan is trying to help, with a new method for uncovering patterns in complicated networks, from football conferences to food webs. This overview contains more details and references about this non-traditional method. It also includes a spectacular representation of the Internet and another image showing a food web at Little Rock Lake."
We see and understand patterns based on the amount of data we can digest (which has gone much further with computers). Knowing that you could always be one data set off defining a pattern makes you wonder if chaos exists at all, hence the replacement of words like chaos with words like "complex".
The uses for this software are astounding. It is, essentially, a breed of software designed to recognize and manipulate social class systems.
... imagine that ... a means of actually targetting campaigns and capers directly to the primary delivery mechanisms of word of mouth among a large group. This software can give you that.
... put this in the hands of the right (wrong?) people, and we could see social revolutions targetted and executed with such blinding accuracy and predictability that most of us simply won't know what hit us ...
... maybe its time to unplug.
Imagine a system which tells you, easily enough, who the 'most popular person for subject ___Y___' is, in your neighborhood? Target a campaign of computer-buying to only -3- folks in an area, and end up blanketing the entire region with tuber-like memes...
PR agencies could use this data to identify the core 'gossip leaders', the ones who have massive impact on multiple peers, and then they could target only those people with their campaigns
There are numerous religious theories, also, on the strengths of individuals and groups and the effect that these social connections have on a movement
This is the danger zone. The moment we start using computers to do qualitative analysis of social dynamics, and then using the data for commercial/religious/nefarious purposes, well
; -- the corruption of government starts with its secrets. a truly free people keep no secrets. --
On the other hand, if one is interested in science. . .
I'd be more interested in seeing the data that gets deleted, not the clumps. This isn't to say that the clumps aren't important, especially if you're trying to rebuild oyster populations in the Chesepeake or some such, but plenty of people will be focusing on those. People have an attraction to like objects and group mechanism.
I have an attraction to the exceptions. That's where the really interesting scientific stuff is likely to be happening, and where the Nobels are most likely to be hiding.
Why is this star off the main sequence? How did it get there, what makes it tick? What relevance might that have to stars that are on the main sequence?
KFG
I have an idea. Phone books of mobile phones form another kind of network. Imagine, A has number of B in his/her phone book. B has number of C. E knows both A and B. Chances are, most of GSM users in Latvia are nodes of this network. But this network can be fragmented as well. I think we could study interesting things about society this way.
:)
We have 7-digit phone numbers and two mobile networks here in Latvia. Data can be stored this way:
6787026 -> 9131415
9131415 -> 5956564
etc...
All we need is one hashtable (or MySQL table) and data collection interface
The problem is more complicated, and you touch on one of the main weaknesses of any system where reputation and feedback in involved.
One aspect of the problem is the granularity by which relationships are defined. In many of the sites there is only one state: "friend or non friend". The real world encompases a number of shades and types, from business acquaintance to personal friend, intimate lover, etc.
Another aspect is the incentive to "game" these systems by increasing your friend count. This inevitably leads people loosening their interpretation such that they increase their visibile friend count. If the number if friends you were linked to was not public, there would be less of this (but you can't do that without breaking some of the functionality of the sites)
People have talked about "winning" at friendster or tribe or orkut - but there is no "winning" in these systems, as there should not be competition.
Last, there is no method for verification of any status between peers. Can you "prove" that so and so is really a friend?
There are others, but these are the main three, and not likely to be solved or addressed any time soon.
I'd be more interested in seeing the data that gets deleted, not the clumps.
Following data clumping, it's really the interactions or the nexus of contact that is interesting. For instance, from a computer science or informational processing perspective, what draws someone to a piece of information? How does one direct information to be most useful? In biological systems, the nexus points are where life happens. For instance, the small molecular fluxes that are constantly providing for molecular signaling, protein synthesis etc.... Information is not lost per se, rather there are information fluxes.
So, to answer your question of stars, it could simply be that a particular star is off the main sequence because of earlier smaller phenomenon that resulted in its appearance much later off the main sequence. Alterations in gravity? Interactions with a binary star? Alterations of proton-proton chains?
Visit Jonesblog and say hello.
Well, on Slashdot, I get fans because people see and like what I post. (Except for one guy, I think he's just trying to max out his friends list.) I set friends based on whether I like and appreciate what they say, and would like to be reminded that I have them set as "friends" whenever they say something I don't necessarily agree with. It helps me consider other points of view.
Granted, its a set of small steps towards understanding the opposing point of view, but it does help broaden my horizons.
It's actually a very useful system.
tasks(723) drafts(105) languages(484) examples(29106)