Detecting Patterns in Complex Social Networks 167
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."
oh my.. the high-school friend one.. (Score:5, Interesting)
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..
Pattern Depth -- does chaos exist? (Score:5, Interesting)
denominator (Score:4, Interesting)
The denominator in these equations should be the peer pressure quotient: the desire of most people to be like most other people.
Astounding social implications. (Score:5, Interesting)
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
Re:Slashdot?..... (Score:5, Interesting)
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
Phone Book Network (Score:5, Interesting)
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
Re:Social Networks are diluted (Score:5, Interesting)
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.
Role-Based Relationship Weights (Score:5, Interesting)
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.
Re:Slashdot?..... (Score:5, Interesting)
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?
Re:Social Networks are diluted (Score:5, Interesting)
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.
Mapping weblog communities (Score:5, Interesting)
Conceptual Clumps (Score:5, Interesting)
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?
Where's the beef? (Score:4, Interesting)
I've been singing the praises of LGL [utexas.edu] 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 the brain (Score:5, Interesting)
- 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.At the University of Michigan... (Score:1, Interesting)
Re:Social Networks are diluted (Score:2, Interesting)
Re:Slashdot?..... (Score:3, Interesting)
In the biological field we may discover Black Smokers, where we learn more about life in general than we do when studying oysters and their ecologies.
It's simply my preference to overtly assume something like Black Smokers are out there somewhere and go looking for them.
In social networks you'll often find the isolated data element (which is to say, person) suddenly explodes as a nexus of contact, or gets absorbed into a clump, or a clump spits something out to the fringes. To me this is, in itself, worthy of attention.
In the example given, for instance, the first thing I want to know is what caused those few interconference games between the physically distant teams to take place at all? It is the nexus of interaction that is interesting to me here, but specifically because that interaction is anomolous.
There is an invisible subnetwork somewhere.
I want to examine it.
KFG
Re:Phone Book Network (Score:3, Interesting)
Re:oh my.. the high-school friend one.. (Score:3, Interesting)
Those dots are lonely.
Six degrees (Score:4, Interesting)
How to train the networking software (Score:4, Interesting)
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.