Archive for March 22nd, 2008

There’s a remarkable feature on Edge.org.  I point it out because it’s robust dialogue about collective behavior.  In particular, the discussion is decidedly not casual agentish, mind-body dualist nor monocasual.  Dr. Couzin is refreshing!  His approach ties very well to analysis of media (collective behavior!)  (Read his other stuff like this essay, too!)

how can a colony decide between two food sources, one of which is slightly closer than the other? Do they have to measure this? Do they have to perform these computations?

We now know that this is not the case. Chris Langton and other researchers have also investigated these properties, whereby individuals just by virtue of the fact that one food source is closer, even if they are searching more or less at random, have a higher probability of returning to the nest more quickly. Which means they lay more chemical trail, which the other ants tend to follow. You have this competition between these sources. You have an interaction between positive feedback, which is the amplification of information—that’s the trail-laying behavior—and then you have negative feedback because of course if you just have positive feedback, there is no regulation, there is no homeostasis, you can’t create these accurate decisions.

There’s a negative feedback, which in this case is the decay of the pheromone, or the limited number of ants within the colony that you can recruit, and this delicate balance of positive and negative feedback allows the colony to collectively decide which source is closest and exploit that source, even though none of these individuals themselves have that knowledge.

Great exposition on the web of contingencies and the feedback loops capable of reinforcing complex behavior that we typically claim is “free choice” like or conscious decision making.

One of the big challenges that still remains, and one that we’re beginning to address—I’m not saying it’s a new question; I’m not saying people haven’t addressed it—is the level at which selection is acting within populations. The view of individual level selection, and selection at the level of genes, of course, holds. But if you consider, say, a school of pelagic fish—these large schools that make these dramatic maneuvers—the individuals are unrelated to each other. They drift around as pelagic larvae, so when their schools are comprised as adults, they’re completely unrelated.And yet the individuals’ functioning is entirely within the context of these schools; you can see the integration of the behavior when they are attacked by predators, you can see why in the ’40s people thought there must be thought transference, must be telekinesis, because of these remarkable maneuvers. We now know that these maneuvers are created by the relatively local interactions among the individuals. But if you take an individual, say, a herring, from the school and isolate it, it will die of stress.It is a bit like taking cells from your body—when you take them outside the body, they are unable to function. Of course it is not as closely integrated as a body, it is not as closely integrated as an ant colony. But there is this high level of integration among unrelated individuals. And in terms of how the genes are going to propagate, genes that allow individuals to function collectively as a group are going to be extremely important. So one has to then begin to think about the level at which selection is actually functionally acting. There is nothing new in terms of the genetics here, but it just in terms of how you begin to understand how the collective behaviors emerge and evolve within these types of systems.

Yes! Selection by consequences. Selection happens at many levels – genetically, epigenetically, and behaviorally.  This is a clearer and more accurate description of collective behavior than some previous discussion on edge.org.

It doesn’t stop there though.  Dr. Couzin reminds us yet again observed behavior emerges from simple, often unexpected, contingencies.

Another example that we’ve been investigating arehuge swarms of Mormon crickets. If you look at these swarms, all of the individuals are marching in the same direction, and it looks like cooperative behavior. Perhaps they have come to a collective decision to move from one place to another. We investigated this collective decision, and what really makes this system work in the case of the Mormon cricket is cannibalism.

You think of these as vegetarian insects—they’re crop pests—but each individual tries to eat the other individuals when they run short of protein or salt, and they’re very deprived of these in the natural environment. As soon as they become short of these essential nutrients, they start trying to bite the other individuals, and they have evolved to have really big aggressive jaws and armor plating over themselves, but the one area you can’t defend is the rear end of the individual—it has to defecate, there has to be a hole there—and so they tend to specifically bite the rear end of individuals. It is the sight of others approaching and this biting behavior that causes individuals to move away from those coming towards them. This need to eat other individuals means you are attracted to individuals moving away from you, and so this simple algorithm essentially means the whole swarm starts moving as a collective.

I mean, really. Think about this… how different is human behavior? (I know, I know, it’s more complex, but…).   Consider the elections, consider online behavior, and consider office politics.  We move towards what we move away from and then you get this behavior that appears collective.  Perhaps in our rush to be anti-brand, unique, a cut above, a stand out, we all come together????

In the human sphere it takes us a great deal of effort and complex cognitive abilities to decide what to do if we are going to decide in a collective. What we can now show is that animal groups, with really simple cognitive powers, can actually perform these types of computations. What we now want to understand is under what conditions these types of cognitive capacities work. How can these animal groups take information from multiple sources; how do they filter out noise and yet amplify weak signals?

Right, we should get some data to back that up!  We are on to it…

Second idea that is interesting is one reason I’m interest in NKS Summer School – simple rules applied over and over and sometimes compounded can generate very complicated behavior.  Sometimes the behavior is so complicated we’re inclined to model it with complex rules.  I want to explore this in depth and showcase it visually.

Dr. Couzin makes a great case for why the study of behavior is key to understanding.

The locust is one of the best-studied organisms for physiology and neurobiology. It is really an amazing model system for looking at these principles. Yet the last time people looked at the swarming behavior of locusts in the lab was in 1954. So there is this dearth of information, and no matter how much you look at a locust, and how much you know about the biology of a locust, you cannot predict what will happen when you start to put these organisms in swarms. …. Issues like the dimensionality of the problem are important; issues such as certain details of the interactions are not important if you want to understand the general principles of how it changes—the phase transition is very important for us in the case of locusts because, as everyone knows, locusts are always around. But then suddenly there is this transition from one state to another almost liquid state—so its driven liquid-type state—where the swarms can become enormous.

He, too, arrives at a similar curiousity in the application of these abstractions to the study of media.

Individuals can have a certain opinion on certain topics, and we can allow individuals to interact across a social network, and of course the social network’s topology is partly defined by what opinions you have. You tend to interact more often with people who have similar opinions to yourself because you are more likely to meet them in your sphere of life. But interacting with people can change your opinions, which can then change your social network, which can change your opinions, so again we have this recursive feedback. And so we are using it to explore these types of properties?I am sure that these types of principles also would apply to understanding dynamics on the Web.

I know there’s some excellent work by Duncan Watts on how individuals buy on-line, or how they judge information that they have on-line, how your judgment of something is dependant on what previous people have said about it. What they used was an on-line music store, where you either have information about what previous people have thought about a song, or you have no information and you just have to rank the song without that previous buyer. This strongly changes people’s behavior because of course when you see what other people have been doing, you can have this autocatalysis, this positive feedback. You can tend to buy into that because you have seen other people do it.

Yes, like so many of my posts, we’ll leave with a simple take away:

We are constantly looking for areas where we can create a more data-driven science behind the spread of these normative behaviors.

And maybe this constant looking is also a spread of a normative behavior?


For info on Duncan Watts weave your way to his Kevin Bacon paper and his take on online music/social trends.  You may want to hit up his wikipedia page for more links.

And Yahoo! research, where he works, has some kickass concepts, publications, apps.

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How convenient!  Slashdot had a lead post about Google ad patents and these patents are all about behavioral targeting.

19. The computer-implemented method of claim 18 wherein actions of the user monitored are selected from a group of user actions consisting of (a) cursor positioning, (b) cursor dwell time, (c) document item selection, (d) user eye direction, (e) user facial expressions, (f) user expressions, and (g) express user topic interest input.

A few other posts around the web lead to other coolish behavior based ad information.

One key aspect of behavior based anything – you need computing power.  lots of it.  This is yet another reason most vertical ad networks, targeted publishers and standard marketers can’t really do behavior based, uber effective advertising campaigns.  They simply lack the raw horsepower.

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Today a little bit of a spat broke out about Federated Media and Glam.

John Battelle wanted to make a general statement when specific ones can easily be made.  Most of these vertical ad networks and vertical ad plays stink.  They aren’t good (or any better than anything else).  They aren’t special for the user, the publisher, nor the marketer.


They aren’t based on behavior.  Most of the targeting and site rollups are based on the terrible panel based demographics and some lame content classifications.  The ad implementations, as John clearly points out, are based on IAB standards – i.e. not behavior.  Unfortunately for John’s argument his company, Federated Media, has the same non-behavior “targeting/verticalization”. He’s got all the tech sites.  That’s not different than Glam.

Recalling the heyday of magazines and cable is hardly a step in the right direction either.  Why?  None of those mediums could deal directly with behavior.  Sure, they influence behavior, but they are mediums that cannot be conditioned in return.  The mags and cable (broadcast in general) depend on a shotgun blast approach.  They have to get in front of you at every newstand, every tv, every checkout lane.  They have to blast you with house promos, drop cards, and numbing outdoor campaigns.  All the ways they had/have to attract you to the content (and ads) is non-responsive, non-personalized.  Luckily these mediums can spend a ton of cash to blast you into readership, viewership and mass appeal.  It’s tried and true, but very expensive.

In short, those experiences aren’t the internet. 

The ad rates weren’t based on the performance of the 2 page ad spread nor any other verifiable metric.  Brand Perception and marketed readership/viewership and sales connections sell those ad rates.  Powerful facets then, powerful now.

Guess what?  The internet doesn’t have mega-brands and most sites ad rates are based on hard to juice metrics (so many ways to verify actual traffic and interaction.).

I do believe high CPM rates are possible.  Integrated experiences built around schedules of reinforcement (conditioning, rewarding, reinforcing) the user and in return other users, editors, the site and so on are worth the money.  These experiences are usually not standard across sites – how can they be?  They need to specific to the service!

Alternate reality, iphone apps, immersive game worlds, user to user games, recommendation ads, mystery games, scavenger hunts, interactive novels…

Note: The only mass market / standard ad that is loosely based on behavior is search ads due to Google’s massive optimization and bidding engine.  The system (prices, creative, number of ads, etc.) morphs constantly to what’s going on and the ads are nearly ubiquitous so they follow the user (reinforce them) regularly (schedules!).

So what’s the next mass market behavioral advertising option?

The next behavior based ad ecosystem is the social network.  Some don’t think its there yet. I disagree.  The social networking apis and the resultant applications are the behavior based ads.  Facebook/MySpace/Hi5/BeBo don’t make money from them yet, but plenty of publishers do.  These “apps” are far more interesting and robust than the ads most agencies, media buyers and marketers stage.   It’s too bad that more brands, companies and products that depend on massive marketing don’t take advantage of these more.  If some of the big companies spent more of their considerable resources on building interesting apps and services, they’d get so much more out of it than the easy to do but usually worthless online ad campaigns and these tired vertical ad networks.

What’s the hold up?

There are a whole set of contingencies preventing online marketers from doing more and running campaigns behaviorally.   Knowledge of behavior, solid analytical approaches, technical skill, time, bucking the system… and more.

There’s simply not enough knowledgeable, creative, competent talent to go around.  And, now, it’s no longer all aggregated at the big five agencies and the big five consumer product companies.

In the heydey of print and broadcast, there weren’t as many variables to pay attention to, not as many options on how, where, when to spend your ad dollars.  There wasn’t even as big an ad market.

Ad budgets are growing, certainly, but not enough to give a growing amount to every publisher, every broadcaster, every newspaper.  TNS predicts a 4.2% US ad spend increase from 07 to 08.   That’s about $340mil extra to split among the cable, network tv, radio, newspaper, magazines and internet options.  Let’s say only 340 new ad outlets become available in 2008 (new websites, cable channels, new magazines, etc. etc.).  That means the only $1 mil for each one of these, assuming existing options don’t grow.  Exactly… ad dollars per publisher, on average, is going to go down over time.

With each publisher getting a smaller slice of the ad pie, they have less money to help marketers try interesting things.  Smaller budgets don’t reinforce greater effort. Less effort doesn’t encourage repeat business.  The free third party metrics sites erase the advantage of heavy hitting sales people.  The rapid trading of talent gives everyone access to the same ideas, same approaches… and so on.

All of this normalizes the options.

Now what?

Rarely do  standard approach turn into a runaway success.  On average, standard approach get standard results.

Vertical sites and vertical networks – most are standard fare.   The High CPMs aren’t going to go to standard fare. The people who can afford high CPMs typically value non-standard options.  Publishers who want high cpms need to put in the effort to develop behavior based experiences.  Users habituate quickly to standard approaches – pattern interrupts are key to engagement. As such, there’s no advantage to advertising in a vertical ad network.  The vertical ad networks exist for the benefit of the publishers, not the users.  Many publishers don’t want to sell their own ads so they let someone else do it.  Turning to a vertical ad network main help run out a budget, but no one has published any data to suggest the performance of vertical networks does any better than advertising on Google.  (why?  well, one of the main factors – most of the vertical sites targeted get 40-80% of their traffic from Google via SEO or SEM.  🙂 )

No, really, now what?

Argh, so much to write about….not enough time!

I’m going to pull out some killer ad campaigns/integrated media as a showcase.  Do you know of any behavior based/game changing ad executions?


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