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."
I don't want to downplay the possible significance, but if you are focusing on the "clumps" (what disparate entities have in common) isn't this akin to taking slices out of a data warehouse? Aligning everything along a single axis?
In the future, I would want to not be isolated from my friends in the Space Station.
Is the pattern of footprints on my bum, back and the top of my head.
I think if the internet was studied as a social network, on might find that someone like Janet Jackson was the core of society :-)
It's hard enough to remember my opinions, never mind the reasons for them..
But do the companies behind these services have any idea of what is hidden inside their complicated networks?
I have often wondered this about Slashdot itself. It would appear to me that Slashdot would provide an ideal means to mine data on complex interactions that may have implications for anything from database design to network load analysis or perhaps the results may even apply to the modeling of biological systems. The owners of Slashdot would be missing something big if they were not examining Slashdot very carefully.
Mapping the Internet only has so many applications, but if one really wanted to make an obscene amount of money, figuring out how to model systems is where it would be.
Visit Jonesblog and say hello.
A researcher at the University of Michigan is trying to help who?
I wonder if this will improve search results? All the fake porn sites will be lumped together, thus, hopefully, taking them out of regular, useful searches.
EVERYDAY IS CATURDAY
In this image..o rks/schoo l.gif
http://www-personal.umich.edu/~mejn/netw
The little single dots on the left..
you have to feel bad for them..
and all the "fringe" people.. they are visibly shown on the fringe..
kind of interesting..
anime+manga together at last.. in real time.
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".
They token rings or Star networks?
From football conferences to food webs: U-M researcher uncovers patterns in complicated networks
SEATTLE---The world is full of complicated networks that scientists would like to better understand---human social systems, for example, or food webs in nature. But discerning patterns of organization in such vast, complex systems is no easy task.
"The structure of those networks can tell you quite a lot about how the systems work, but they're far too big to analyze by just putting dots on a piece of paper and drawing lines to connect them," said Mark Newman, an assistant professor of physics and complex systems at the University of Michigan.
One challenge in making sense of a large network is finding clumps---or communities---of members that have something in common, such as Web pages that are all about the same topic, people that socialize together or animals that eat the same kind of food. Newman and collaborator Michelle Girvan, a postdoctoral fellow at the Santa Fe Institute in Santa Fe, New Mexico, have developed a new method for finding communities that reveals a lot about the structure of large, complex networks. Newman will discuss the method and its applications Feb. 15 at the annual meeting of the American Association for the Advancement of Science in Seattle.
"The way most people have approached the problem is to look for the clumps themselves---to look for things that are joined together strongly," said Newman. "We decided to approach it from the other end," by searching out and then eliminating the links that join clumps together. "When we remove those from the network, what we're left with is the clumps."
The researchers tested their method on several networks for which the structure was already known---college football conferences, for example. In college football, teams in the same conference face off more frequently than teams in different conferences. When inter-conference games do occur, they're more likely to be between teams that are geographically close together than between teams that are far apart. Plugging in information on frequency of games between pairs of teams in the 2000 regular season, Newman and Girvan tested their method to see if it could correctly sort the colleges into conferences. "There were a few cases where it made mistakes, but it got well over 90 percent of them right," said Newman. "It gave us the structure we were expecting, so that was encouraging."
Newman and Girvan---and other researchers who've learned about their work---have gone on to apply the technique to systems where the structure is not as well understood, looking at everything from networks of Spanish language web logs to communities of early jazz musicians to a food web of marine organisms living in Chesapeake Bay.
"Networks and other systems that we study are becoming increasingly large and complicated these days," said Newman. "New methods like this help us to make sense of what we see and to understand better how things work."
###
For more information:
Mark Newman -- http://www-personal.umich.edu/~mejn/
American Association for the Advancement of Science -- http://www.aaas.org/
Santa Fe Institute -- http://www.santafe.edu/
I heard of account deletion because of faked/spoofed "delete my account" mails.
Remember to check their Terms :
By submitting, posting or displaying any Materials on or through the orkut.com service, you automatically grant to us a worldwide, non-exclusive, sublicenseable, transferable, royalty-free, perpetual, irrevocable right to copy, distribute, create derivative works of, publicly perform and display such Materials.
They invented their own licencse. What do you think if Micro$oft buyes Google ? .aspx files....
And its based on
I dont want to know how they care about data privacy
I know someone with 400 friends in his network on friendster. Yet he strongly claims to have never talked to any of these people. How in the world did these people end up on his list?
There should be some kind of requirements forcing you to somewhat communicate with these people, otherwise they should be off your list.
These social networks are giving "friends" a real bad definition.
The blue node (left center) in this diagram was gettin' some action!
TK
Social network analysis has been around for years in social science, so I don't see what is new here. And before anyone complains, yes, these nice pictures are also far from new.
The denominator in these equations should be the peer pressure quotient: the desire of most people to be like most other people.
illegitimii non ingravare
they've solved the k-Clique problem, since it's NP complete. ALL YOUR PASSWORDS ARE BELONG TO US!
personal information pyramid schemes?
demographic data Amways*?
commercial marketing's petri dishes for growing advertising targets?
*a US multi-level marketing scheme
The researchers tested their method on several networks for which the structure was already known---college football conferences, for example. In college football, teams in the same conference face off more frequently than teams in different conferences. When inter-conference games do occur, they're more likely to be between teams that are geographically close together than between teams that are far apart. Plugging in information on frequency of games between pairs of teams in the 2000 regular season, Newman and Girvan tested their method to see if it could correctly sort the colleges into conferences. "There were a few cases where it made mistakes, but it got well over 90 percent of them right," said Newman. "It gave us the structure we were expecting, so that was encouraging."
Finally, something that can help me understand the divisions in the NHL. I've been confused ever since they got rid of Smythe, Norris, and all the rest...
Stop by my site where I write about ERP systems & more
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. --
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
I didn't know Jackson Pollack designed the internet.
I wonder whether they'll finally be able to (dis)prove the hypothesis that everybody knows everybody else within six (or however many) degrees of separation.
Then again, most people will probably have a connection to Nigeria due to the certain organ-lengthening drug that they are so famous for.
I remember the first maps of the Internet showed that certain nodes concentrate power in terms of the number of connections they make. Google, perhaps.
A quick reading on Zipf's Law shows that many natural systems (and many artificial ones that obey similar laws of construction and equilibrium) observe 'power rules' where the distribution of power is inverse to the number of entities at any level.
Surprising that earthquakes, cities, businesses, follow the same rules. And yet quite meaningless in any direct sense because we can't manipulate these rules, only observe them.
Human social networks also follow rules that I suspect are quite simple and possibly similar to Zipf's Law. For instance, a person can only maintain a finite number of contacts (technology may increase this number but it remains finite at any given time). Any new contact coming in displaces an existing contact. So a single person's contact list will follow a power law: twice as many contacts used half as often, ten times as many contacts used a tenth as often...
Mapping a contact network would need to take the importance of each contact into account. I may have my grandmother in my list, but I speak to her once a year. My accountant - every week. My wife - twice a day. My girlfriend - every hour.
Next: the differences between individuals in terms of how much time/skill they invest in networking. Gender differences... women do this much more and better than men, in general. Age differences... younger men do it less well than older men. Wealth differences... richer people do more networking, I'd suspect, until a certain point when they start to delegate it. Very poor people do very little networking.
So, the network is not a flat map. It's got two dimensions for the lines, but each line has a thickness, and each node (individual) has a size.
Finally, I'd suspect that the network also maps power in terms of social success. Those people with the most powerful networks (a recursive definition: the networks which involve the most powerful people) will also be the most successful socially / financially.
But they may not be the happiest.
Large scale networks have limitations because real relationships are complex. The notion of A-is-a-friend-of-B or A-trusts-B is too simplistic for large scale networks. These connectivity relationships are not transitive in real-life (A-trusts-B & B-trusts-C does not imply A-trusts-C)
Rather, the network needs some form of role-based assertion or qualification of the relationship. I know friends that I like to go hiking with, but that I disagree with politically. I know people that I do trust to recommend software, but don't trust to recommend a restaurant. And if I trust person B to recommend software, I would probably only trust that person B to recommend another person C in a limited set of domains (like software or technical issues). Thus the real relationship is more like person-A-trusts-person-B-for-role-C.
Such a scheme of role-defined relationships could be self-organizing or predefined. The self-organizing approach would look for disjoint clusters of members in a network or use semantic analysis of the messages passed between people to infer a set of role-clusters. Predefined relationship might be OK, but could become unwieldly if the network creators force people to answer a long multiple-choice test about every relationship.
Two wrongs don't make a right, but three lefts do.
Why is it that many /.'ers are so concerned with their privacy in some cases, such as pay pal, ebay, etc, and yet have no problem giving another company their contact info and the contact info of everyone they know? It seems that digitizing social networks (ala friendster) really opens you up for privacy abuse. These companies could, frankly, really mess up your life if they decided to do such a thing, or if a hacker broke in and did such a thing.
Are we sure this is Slashdot?
Oh, there it is, "..to food webs".
- In Capitalist America, law violates YOU!
Check out the "highschool friendships" diagram.
I think I was the yellow dot on the far left.
In all matters of opinion, our adversaries are insane. -Oscar Wilde
I have been thinking about concept clumps - kind of similar to social clumps and cluster - but relating things that are based around similar ideas of information that they are trying to convey.
:)
Similar in the way that grokker clumps navigable areas together, it would be interesting to instead clump things together based on the relations of the meaning of the information they contain.
For example, lets say that you are reading an article on any given site. You would be able to highlight a phrase, a word or a sentance, then look that term up in context. This is different than simply googling the term in that you are looking for the context of the term as opposed to a concrete definition.
so if you were reading an article regarding the legal take over of a company by intel, you would be able to easily search for articles writen that involve intel in any other litigation, with results containing intel involved in purchases or sales of companies and their technologies coming to the top of the list...
obviously there is a lot more in this required to accomplish it - so Ill just stop here before giving it all away.
The main point being that this type of searching is easily applicable to understanding relationships in social networks as far as identifying how common intrests are shared.
The clustering of attractions and dislikes to profile trends and personalities in any given demographic are made especially easy in systems such as friendster and orkut. By having people OPT-IN to the deepest marketing database available and provide you with all the details of not only the things they like (under the guise of sharing yourself with the others in the community) AND showing you what other people they are connected with who share common interests is one of the biggest social hijacks ever.
Just when you thought marketing was a dead science that is too transparent to have any real impact, social networks arise to provide marketing data on an astounding level.
[don tin foil hat]
Just wait till they are able to correlate all this info with DNA profiles
Not that this is bad per se, but it is a fact taht this info will be the next gold standard in market research where marketing will move to a social promotion system.
I think that the goal here is the promotion of product will largely come from people advertising their likes of a product through their profiles and communications with friends online.
It will be very easy for a group of people to communicate things (it already is) that are of interest to their social networks. Like on person telling the other 65,000 friends they have how they jsut experienced product Y, and that everyone should try it....
interstingly, will we see fakesters made specifically to spam the other friends with testimonial like adverts for products they are trying to introduce to a specific demographic?
For those who are interested, a PDF of the paper mentioned in the article is here. Running time is O(n^2) versus O(n^3) for previous algorithms, so don't go applying it to the Google cache just yet.
I'm sure there's something really cool these guys are doing, but there is a very strong distinction between Big F*cking Huge Graphs (like we see a bunch of in the links) and Big F*cking Graph Analysis using some new technique, which isn't really clearly anywhere in there.
I've been singing the praises of LGL as of late, pushing it into the Opte project (mass internet viz) and such, but truly the interesting applications involve analysis -- and where's the beef on that in this story?
--Dan
And his name is Kevin Bacon.
I mean, the more you analyze them, the more bullshit in our society will be realized, the more cynical you'll get, and the more antisocial you'll become.
"Ignorance is bliss" never applied better than to the study of people.
Unfortunately, then only pattern in my social network is the singleton pattern.
neither myself or any of my friends (all of whom are very net-savvy) do not use it and have no intentions of using it.
- the wiring of it (topology) can gives a lot of insight on how it works and can even explain some emerging side effects.
- it evolves with time - new connexions are made between nodes everyday, and we observe self-optimization.
- the information that is communicated within the network itself is also pretty important. Actually, this is not only the tracer from which we derive its topology and its evolution, but also the very meaning of it.
There is something way too similar about social networks, internet and the brain that really troubles me.Sounds to me like the TIA.
I'd like to check out the Orkut network--but have no friends (on it!). Would anyone be my friend? Just invite orkut@runar.net :)
Thanks
Thia is all pretty standard in marketing now; give the popular kids a new toy and then watch all the other kids want it. It really doesn't take a computer to figure out who everyone thinks is popular, it kind of what we humans do.
And we are already in the danger zone, you really think the big advertisers have been ignoring this kind of thing?
A blog about stuff.
I go to the University of Michigan, and they even have classes where students examine social networks. It's interesting, but it's just used as an excuse to write a paper. It's engineering 100, a/k/a english for engineers.
only takes into account a particular type of relationship. try mapping much more complex (and relevant) concepts: influence, for instance. society isn't friendster; if it were so your relevance in society would basically boil down to how many people are 'in your network', so to speak.
I'm that little disconnected node way over in the dark corner. :-(
--- Ban humanity.
You did Kevin Bacon? I heard he was GAYER THAN AIDS.
you can see your social network online at Huminity . They use a simple Google like interface (Google of people?) and show nodes and links maps of social networks. i think its the only "open" social network since in others u need to register before you can take a peek.
I'm New Here
A very interesting link in this regard can be found on http://www.verbumvanum.org/shirky
And he's sharing three of them with the same guy. Smells like frat spirit.
illegitimii non ingravare
I'm in the middle of reading _Nexus_ by Mark Buchanan. One of the topics he covers is the work by Mark Granovetter that discusses links in a social network. One thing I found interesting was that weak links, those from friends-of-friends or casual associates, do more to tie together a network than the local, strong links. The reasoning is that local links tend to be more isolated: your friends will have similar interests and know many of the same people. Links to distant nodes will thus tend to be more "ordered" and require more steps to reach that node. Weak links will act as a shortcut between disparate groups.
The interesting thing to note about these social networks (which seems to have been overlooked) is that everyone will put different weights on what is important when deciding their social cirlcles. You can have ten people, with each having all the same interests. Soccer, computers, ramen noodles, Coors Light, Chihuahuas, and small-waisted women with big breasts. Yet each of these people will probably rank each differently. While one may go right up to Chihuahua lover at a party and strike up a conversation, another will go straight to the kitchen and see who else is looking at the ramen noodle collection.
Basically, we have to find a way to "train" the software. It's not going to be easy. Training the TiVo still doesn't give you the best results. The personality compatibility tests sure are interesting, eh? Who here has been matched with the perfect roommate in college? Yet I haven't seen much yet on the weights of interests, just discussions about clusters of tight-knit social groups.
"He uses statistics as a drunken man uses lampposts...for support rather than illumination." - Andrew Lang
I wonder whether they'll finally be able to (dis)prove the hypothesis that everybody knows everybody else within six (or however many) degrees of separation.
This was first proposed in 1967 by social psychologist Stanley Milgram, (in)famous for his shocking experiments on human obedience, which inspired Peter Gabriel to create the subversive sing-along "We Do What We're Told", a.k.a. "Milgram's 37".
This paragraph brought you by a flock of hyperlinking free associators with Erds number 4.
Be faithful to your obsessions. Identify them and be faithful to them, let them guide you like a sleepwalker. JG Ballard
Introvertster
http://www.sfu.ca/~insna/
R L&_cdi=5969&_auth=y&_acct=C000050221&_version=1&_u rlVersion=0&_userid=10&md5=0dbd43b8d4784bc1532be7b 6c056be81
INSNA is the professional association for researchers interested in social network analysis.
http://www.casos.cs.cmu.edu/
CASOS brings together computer science, dynamic network analysis and the empirical study of complex socio-technical systems. Computational and social network techniques are combined to develop a better understanding of the fundamental principles of organizing, coordinating, managing and destabilizing systems of intelligent adaptive agents (human and artificial) engaged in real tasks at the team, organizational or social level. Whether the research involves the development of metrics, theories, computer simulations, toolkits, or new data analysis techniques advances in computer science are combined with a deep understanding of the underlying cognitive, social, political, business and policy issues.
http://www.cmu.edu/joss/
The Journal of Social Structure (JoSS) is an electronic journal of the International Network for Social Network Analysis (INSNA). It is designed to facilitate timely dissemination of state-of-the-art results in the interdisciplinary research area of social structure. It publishes empirical, theoretical and methodological articles.
JoSS publishes manuscripts that are focused on social structure-on the patterning of social linkages among actors. These actors could be comprised of different types or levels or analysis, such as animals, humans, artificial agents, groups or organizations. INSNA was founded on the premise that the behavior and lives of social entities are affected by their position in the overall social structure. By examining the etiology and consequences of structural forms overall, of the location of entities within these structures, and of the formation and dynamics of ties that make up these structures, INSNA hopes to learn about the parts of behavior that are uniquely social.
http://www.sciencedirect.com/science?_ob=JournalU
Publication of social networks papers.
how is this thought compatible with your sig? am i interpreting things correctly? how can you both remain non-anonymous, and retain any ability to sell data about yourself whatsoever? if you are anonymous there is little you can do(there is some, but not much) to make inferences about the you when there is a large pool of anonymous agents. right? whereas, if you have named induviduals in a pseudopublic database... inferences can be made just by observing this database..this is a passive process, and you would have to actively fight against it from occurring, if you could at all, which i doubt. the information about you is necessarily then being documented, and broadcast, and asking money for it is like asking money for the photons being interpreted by the brains of people who are looking at you when you are physically nearby them.
as for the topic? i think the first thing to note is the finiteness of human lifespans, and the ability to only interact with so many humans in a lifetime.
or has slashdot/someone paid you to disclose your name? or do you really think that your screen-name hides your true identifying number?(i doubt this)
Pseudopublican party for president!
GENERATION 26: The first time you see this, copy it into your sig on any forum and add 1 to the generation.
and then you get the screwed up freaks who's main focus as far as freindship goes is 'a person who is not actively trying to kill or harm me in any way'. yes. that was my definition once upon a time. and i heard it echoed later on in a couple of places independant of my home town, once i found the internet. surely, the internet has changed the entire dynamics of freindship, as i thought that most of the people out there were totally against me, when in reality, they were just trying to save themselves face by picking on or just plain not supporting the freak. now with the internet the 'freaks' can 'team up' with eachother...so there HAS to be a new level of freindship screw-ed into the worldview of even the most unfreindly. right?
GENERATION 26: The first time you see this, copy it into your sig on any forum and add 1 to the generation.
These maps need a you are here arrow.
Furthermore, read a few books on emergence (like Kevin Kelly's "Out of Control"). Might as well also pick up and read Wolfram's "A New Kind of Science"...
I have said it before and I will say it again: Taken together, the knowledge within these three books could very well lead to some amazing breakthroughs in many of the sciences, in particular cognitive sciences and genetics. Even if some of the theories prove to be wrong, I think there is enough there to be a springboard for someone else - please read and decide for yourself!
Reason is the Path to God - Anon
The unspoken "Why?" of all of this is that companies are trying to understand our social connectedness as a way to SELL us things.
Why use the scattershot TV ad to get us to buy a new car when they can simply allow the desirability of ownership trickle down the social food chain?
This is "Keeping up with the Joneses" taken to perfection. Once it is calculated which other individual or group we all choose to imitate, you find that there are only 30 people in the world who have to be given that new promotional edition MP3 player and soon everyone else in the world will HAVE to have one too. How Pavlovian!
The only problem I have with this way of thinking is that it continues down the path we are on of valuing everything except quality in product selection. It assumes (probably accurately) that many of us do what we do by imitation rather than making our own choices based on our own thought processes.
No need to enslave the masses when you can tap into their programming and get them to do what you want willingly. 2084, here we come.
(use of this technology in politics and it's ramifications left as an exercise for the reader)
A researcher at the University of Michigan... ... a bright, promising freshman by the name of Hari Seldon....
-Styopa
Also, like a dirty Where's Waldo, can you spot the bis? I can see six. (Only two of whom, I might add, enjoy a stereotypically large number of partners.)
Aside: what would the explanation for the big cycle be in social terms? I see only three other cycles, but two of them are caused by frat spirit so they don't count.
And an example to illustrate the way networks work.
The Capo di Capo is lying ill in bed. He speaks to his three trusted sons, who run The Business. Julio handles mainly drugs and girls, on the lower east side. Frankie does weapons and gambling, city-wide. Ernesto handles administration and corruption, the 'cost center' as he calls it.
The Capo di Capo, though 80 years old and hardly able to move, controls his empire with an iron will. He plays his three one against the other in a fine game that ensures neither gets too bold. He has a few years left to live, and means to keep his empire together, one more year, one more year.
Just one old man, only talking to his three sons controls millions of people: their very lives depend on him one way or another. If he becomes moral and decides to stop selling the drugs, this would change the lives of half the city.
One person, just three points of contact, leading to a network of millions.
-----
The day will come when a simple scan and cross-reference of everyone's agenda and contact list will highlight immediately the powerful men in a city or country. Half will be politicians, the other half mafia bosses.
The programmer, meanwhile, who invents this program, has every interest in remaining an anonymous coward.
Is that only me, or does that sound a lot like TIA? Ask yourself the question: who will benefit from such a technology? Who has the reasources to employ it? The ones that come to my mind are the NSA, Time/Warner, Banks, etc. Is this really a good thing?
Let me quote Wau Holland on this one: "Wem gehoeren unsere Daten?" (engl.: "Who owns our data?") Who has what rights to process them, and in what ways? Do I have a say in what is done with "my" data (i.e. the data i "generate" just by being myself)?
Datamining is increasingly becoming an issue with respect to privacy (duh.) Is there anything that we meight do to stop this world from becoming a rather sophisticated version of 1984? Do i sound paranoid? Well, maybe i am. But i belive we also have to think about the implications of new "cool technology". Just going "oooohhh, something shiny" won't do in the long run.
I have discovered a truly remarkable sig which this 120 chars is too small to contain.
These people rediscovered clustering methods from the 1950's.
"It also includes a spectacular representation of the Internet"
/. before...
hmmm... that represenation was taken from here, and its a snapshot from 1999 (sic). Also, i'v seen that before (aktually, i have one of those as a desktop image). I think it was on
are we being s^Htold old news? I mean, really old, not just your regular slashdot-dupes....
Also: look at theis galery of network images. Look at "Highschool Dating". Few cicles? No gays? something is wrong here... On the other hand, look at "Highschool Friendship": the four lonely ones to the left... what dot you think are the chances that thous four are still living in their parents basements and are reading slashdot?...
I have discovered a truly remarkable sig which this 120 chars is too small to contain.
... to develop a psychohistory model!
The Buffy sex chart is far more interesting! It has real names and everything!
Barabasi and his group at Notre Dame have been pioneers in this area, especially their finding on the "diameter of the Web"!
You can have a look at his work at his website.
A good place to start could be this presentation (ppt file ~ 9.6MB) that seems to be more for the public audience.
I totally second the recommendation for Albert-Laszlo Barabasi's "Linked".
[o]_O
The Foundation stories were great. Read 'em.
-- 'The' Lord and Master Bitman On High, Master Of All
one could think that networking people
/., CNN, Yahoo mostly share at least
and ideas might give rise to a kind
of distributed "super-intelligence".
each brain enhancing the next one, so
to speak, like putting one brick on-top
of another and reaching never before seen
hights of intelligence.
this doesn't seem to be true at all.
it seems, that people using the internet
just try to find like-minded people
with whoem they can just share the same
state of mind and not challenge each other.
like micheal crichton pointed out in
his book "jurassic park 2" large
networks seems to have a synchronization
effect. people become the same.
in german we call this "gleichschaltung"
and it was extensively used in the
second world war in germany.
the web has turned grosely commercial
and suddenly ol' school netizens
(you're one if you "surfed" the web
on 2400 baud modem) find themself
in a TV like environment. not a bad
thing (since the internet is interactive)
but the interactivity has boiled down
to a virtual state. no unique information
is added statically, but information
is shared thru dynamic means (IM, email.)
turn off the computer and it's gone.
if you look at 90% of the "static(*)" webpages
there's a very high amount of redundancy.
even
one article the same everyday.
you can argue that newspaper do this too,
but the internet isn't a classical media.
but it seems, the daily use observed, is
going to turn it into one.
but not to worry, there will always be
some "dark, novel" alley in the internet
where you'll find some really unique
NEW information. and i find all this
redunancy makes the search for these
lost "data-island of atlantis" much
more cyberspacy!
(*)static meaning the bits and bytes are on
a harddisk.