I posted a link to this online review of:
"The Tipping Point: How Little Things Can Make a Big Difference" by Malcom Gladwell
to my weblog a few weeks ago, but for some reason Google didn't pick it up in the index. So here it is again.
The books main ideas are:
Tipping Point - Net Version
HappyFeet has made the best effort possible to put these items in some form of coherent order. This book used alot of marketing/business angles. I chose to replace those examples, etc. with art, creativity, and revolution. Use this to make the truth bloom.
There are exceptional people out there who are capable of starting epidemics. All you have to do is find them. With an epidemic, a tiny majority of the people do the work. Once critical factor in epidemics is the nature of the messenger. Messengers make something spread.
Word of mouth is still the most important form of human communication. Rumors are the most contagious of all social messages. Connectors
- "Interactional synchrony": human interaction has a rhythmic physical dimension. We dance to each other's speech…we're perfectly in harmony.
- Motor mimicry: we imitate each other's emotions as a way of expressing support and caring and, even more basically, as a way of communicating with each other. Emotion is contagious. "Senders" are very good at expressing emotions and feelings. They are far more emotionally contagious than the rest of us.
There is a simple way to package information that, under the right circumstances, can make it irresistible/sticky and compels a person into action. All you have to do is find it. In order to be capable of sparking epidemics, ideas have to be memorable and move us into action. Content of the message matters too.
We don't necessarily appreciate that our inner states are the result of our outer circumstances. We are more than just sensitive to changes in context. We're exquisitely sensitive to them. And the kinds of contextual changes that are capable of tipping an epidemic are very different than we might ordinarily suspect. The impetus to engage in a certain kind of behavior is not coming from a certain kind of person but from a feature of the environment.
"There seems to be some limitation built into us either by learning or by the design of the nervous systems, a limit that keeps our channel capacities in this general range (i.e. the human minds inability to comprehend things beyond sets 7)" —George Miller "The Magical Number Seven"
"The figure of 150 seems to represent the maximum number of individuals with whom we can have a genuinely social relationship, the kind of relationship that goes with knowing who they are and how they relate to us. Putting it another way, it's the number of people you would not feel embarrassed about joining uninvited for a drink if you happened to bump into them in a bar." —Robin Dunbar,
Starting epidemics requires concentrating resources on a few key areas. Your resources ought to be solely concentrated on the Connectors, Mavens, and Salesmen.
The world does not accord with our intuition. Those who are successful at creating social epidemics do not just do what they think is right. They deliberately test their intuitions.
What must underlie successful epidemics, in the end, is a bedrock belief that change is possible, that people can radically transform their behavior or beliefs in the face of the right kind of impetus. Tipping Points are a reaffirmation of the potential for change and the power of intelligent action. Look at the world around you. It may seem like an immovable, implacable place. It is not. With the slightest push; just in the right place; it can be tipped. NOTES, ETC.
Diffusion model: a detailed, academic way of looking at how a contagious idea or "product" or innovation moves through a population.
It's basically to see how complex human systems really work. It can be a project team in an organization, or a terrorist team, or it could be a community where a virus is spreading, and figuring out how and why it's spreading a particular way. It allows us to look at and map what are normally invisible dynamics inside a community. Once you know about it and start thinking about it, you start to realize there's a lot of relational data out there. If you start putting it together piece by piece, you put together an interesting picture, more than any of the pieces by itself.
That's what I did with that terrorist network map. Everyone was talking about terrorist networks, but no one was putting it together. So I slowly started gathering data from various sources, and with a couple hundred data points, it started looking like something.
Initially there was a thing called a socio-gram, which Jacob Levi Moreno developed in the early 30s. These were drawn out by hand. You would observe a group, and draw a diagram, where the circles are the people, the lines are who talked to who. Other researchers started to follow.
(ed.: For a good history on the development of social group visualization, read "Visualizing Social Groups," (.PDF) by leading social network theorist Linton C. Freeman. And dig his hair and shirt!)
Visual Neighborhood. Blogstreet launches visual neighborhood.  Blogstreet just launched a new tool that uses Java to let you view your Blogstreet "neighborhood" and click on your neighbors to expand and see their neighborhoods, etc. You get the idea. The tool is on their site and the developer, Veer, blogs about it. [Joi Ito's Web -> Ross Mayfield's Weblog]1:07:22 PM  |
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Jon Udell summarizes Power Laws and Scale-free networks:
8:41:36 AM |
| Origin of power laws Abstract: Power laws are characteristic of randomly distributed values that come |
The richness of human languages is a fine-tuned compromise between the needs of speakers and of listeners, explain Ramon Ferrer i Cancho and Ricard Solé of the Universitat Pompeu Fabra in Barcelona. Just a slight imbalance of these demands prevents the exchange of complex information, they argue.
... Human languages, say the duo, seem to sit right on this sudden change. When it happens, the frequency of word usages develops a distinctive mathematical form, called a power law. The power law disappears on either side of the communication jump.
It has been known since the 1940s that human languages do indeed show just this kind of statistical distribution of word usage - the social scientist George Kingsley Zipf spotted the power-law behaviour. But it has never been satisfactorily explained before, although Zipf himself speculated that it might represent some kind of "principle of least effort".
Doc Searl on Clay:
Like Dave, I wish Clay Shirky would start a blog too. I know it's not Clay's style, just like it's not, say, Jerry Michalski's (although Jerry has a blog and Clay doesn't). Some things are best learned by doing, and it strikes me that in the absence of doing Clay hasn't learned how poorly the power story applies in the blogosphere.
In Power Laws, Weblogs, and Inequality, Clay runs blogging through the power law mill, and the result is akin to running a cat through a Cuisinart: you get easily measured stuff that bears no resemblence to the subject of the study.
One of his points:
Given the ubiquity of power law distributions, asking whether there is inequality in the weblog world (or indeed almost any social system) is the wrong question, since the answer will always be yes. The question to ask is "Is the inequality fair?" Four things suggest that the current inequality is mostly fair.
The inequality Clay talks about — the fact that some of us are graced with more links and readers than others — is of a purely numerical sort. It says nothing about why people write blogs, and why readers read blogs.
To illustrate my own point here, go sort your email by name. Is there a power curve there? If there is, does it matter?
For many of us (me included), blogs serve a kind of public email function. Since a bunch of correspondents wrote to me asking for my opinion about Clay's essay, I'm writing back to the bunch of them, plus everybody else who cares (a sum which, as a percentage of the true everybody, verges on zero).
.......
Launching good new blogs is no less easy than it ever was, and good new blogs grow no slower than they ever did. Blogging tools like Trackback and Technorati don't signal the drift of blogging toward some kind of portalesque middle-distance, but rather a constant increase in the number and variety of tools available to the practice — plus the constant change those tools bring to the practice itself. Blogging is radically different than it was six months ago. Technorati alone has changed my blogging life, largely by acquainting me with all the worthy blogs with which I had previously been unfamiliar.
The whole blogosphere is characterized by a high exponent of the experimenter effect. To borrow from Forrest Gump, blogging is as blogging does, and that changes every time somebody blogs something interesting that somebody else blogs about. It's wild.
| First published February 8, 2003 on the 'Networks, Economics, and Culture' mailing list. Subscribe to the mailing list. |
| Version 1.1: Changed 02/10/03 to point to the updated "Blogging Ecosystem" project, and to Jason Kottke's work using Technorati.com data. Added addendum pointing to David Sifry's "Technorati Interesting Newcomers" list, which is in part a response to this article. |
A persistent theme among people writing about the social aspects of weblogging is to note (and usually lament) the rise of an A-list, a small set of webloggers who account for a majority of the traffic in the weblog world. This complaint follows a common pattern we've seen with MUDs, BBSes, and online communities like Echo and the WELL. A new social system starts, and seems delightfully free of the elitism and cliquishness of the existing systems. Then, as the new system grows, problems of scale set in. Not everyone can participate in every conversation. Not everyone gets to be heard. Some core group seems more connected than the rest of us, and so on.
Prior to recent theoretical work on social networks, the usual explanations invoked individual behaviors: some members of the community had sold out, the spirit of the early days was being diluted by the newcomers, et cetera. We now know that these explanations are wrong, or at least beside the point. What matters is this: Diversity plus freedom of choice creates inequality, and the greater the diversity, the more extreme the inequality.
In systems where many people are free to choose between many options, a small subset of the whole will get a disproportionate amount of traffic (or attention, or income), even if no members of the system actively work towards such an outcome. This has nothing to do with moral weakness, selling out, or any other psychological explanation. The very act of choosing, spread widely enough and freely enough, creates a power law distribution.
A Predictable Imbalance
Power law distributions, the shape that has spawned a number of catch-phrases like the 80/20 Rule and the Winner-Take-All Society, are finally being understood clearly enough to be useful. For much of the last century, investigators have been finding power law distributions in human systems. The economist Vilfredo Pareto observed that wealth follows a "predictable imbalance", with 20% of the population holding 80% of the wealth. The linguist George Zipf observed that word frequency falls in a power law pattern, with a small number of high frequency words (I, of, the), a moderate number of common words (book, cat cup), and a huge number of low frequency words (peripatetic, hypognathous). Jacob Nielsen observed power law distributions in web site page views, and so on.
We are all so used to bell curve distributions that power law distributions can seem odd. The shape of Figure #1, several hundred blogs ranked by number of inbound links, is roughly a power law distribution. Of the 433 listed blogs, the top two sites accounted for fully 5% of the inbound links between them. (They were InstaPundit and Andrew Sullivan, unsurprisingly.) The top dozen (less than 3% of the total) accounted for 20% of the inbound links, and the top 50 blogs (not quite 12%) accounted for 50% of such links.
 Figure #1: 433 weblogs arranged in rank order by number of inbound links. The data is drawn from N.Z Bear's 2002 work on the blogosphere ecosystem. The current version of this project can now be found at http://www.myelin.co.nz/ecosystem/. |
The inbound link data is just an example: power law distributions are ubiquitous. Yahoo Groups mailing lists ranked by subscribers is a power law distribution. (Figure #2) LiveJournal users ranked by friends is a power law. (Figure #3) Jason Kottke has graphed the power law distribution of Technorati link data. The traffic to this article will be a power law, with a tiny percentage of the sites sending most of the traffic. If you run a website with more than a couple dozen pages, pick any time period where the traffic amounted to at least 1000 page views, and you will find that both the page views themselves and the traffic from the referring sites will follow power laws.
 Figure #2: All mailing lists in the Yahoo Groups Television category, ranked by number of subscribers (Data from September 2002.)
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Rank Hath Its Privileges
The basic shape is simple - in any system sorted by rank, the value for the Nth position will be 1/N. For whatever is being ranked -- income, links, traffic -- the value of second place will be half that of first place, and tenth place will be one-tenth of first place. (There are other, more complex formulae that make the slope more or less extreme, but they all relate to this curve.) We've seen this shape in many systems. What've we've been lacking, until recently, is a theory to go with these observed patterns.
Now, thanks to a series of breakthroughs in network theory by researchers like Albert-Laszlo Barabasi, Duncan Watts, and Bernardo Huberman among others, breakthroughs being described in books like Linked, Six Degrees, and The Laws of the Web, we know that power law distributions tend to arise in social systems where many people express their preferences among many options. We also know that as the number of options rise, the curve becomes more extreme. This is a counter-intuitive finding - most of us would expect a rising number of choices to flatten the curve, but in fact, increasing the size of the system increases the gap between the #1 spot and the median spot.
A second counter-intuitive aspect of power laws is that most elements in a power law system are below average, because the curve is so heavily weighted towards the top performers. In Figure #1, the average number of inbound links (cumulative links divided by the number of blogs) is 31. The first blog below 31 links is 142nd on the list, meaning two-thirds of the listed blogs have a below average number of inbound links. We are so used to the evenness of the bell curve, where the median position has the average value, that the idea of two-thirds of a population being below average sounds strange. (The actual median, 217th of 433, has only 15 inbound links.)
Freedom of Choice Makes Stars Inevitable
To see how freedom of choice could create such unequal distributions, consider a hypothetical population of a thousand people, each picking their 10 favorite blogs. One way to model such a system is simply to assume that each person has an equal chance of liking each blog. This distribution would be basically flat - most blogs will have the same number of people listing it as a favorite. A few blogs will be more popular than average and a few less, of course, but that will be statistical noise. The bulk of the blogs will be of average popularity, and the highs and lows will not be too far different from this average. In this model, neither the quality of the writing nor other people's choices have any effect; there are no shared tastes, no preferred genres, no effects from marketing or recommendations from friends.
But people's choices do affect one another. If we assume that any blog chosen by one user is more likely, by even a fractional amount, to be chosen by another user, the system changes dramatically. Alice, the first user, chooses her blogs unaffected by anyone else, but Bob has a slightly higher chance of liking Alice's blogs than the others. When Bob is done, any blog that both he and Alice like has a higher chance of being picked by Carmen, and so on, with a small number of blogs becoming increasingly likely to be chosen in the future because they were chosen in the past.
Think of this positive feedback as a preference premium. The system assumes that later users come into an environment shaped by earlier users; the thousand-and-first user will not be selecting blogs at random, but will rather be affected, even if unconsciously, by the preference premiums built up in the system previously.
Note that this model is absolutely mute as to why one blog might be preferred over another. Perhaps some writing is simply better than average (a preference for quality), perhaps people want the recommendations of others (a preference for marketing), perhaps there is value in reading the same blogs as your friends (a preference for "solidarity goods", things best enjoyed by a group). It could be all three, or some other effect entirely, and it could be different for different readers and different writers. What matters is that any tendency towards agreement in diverse and free systems, however small and for whatever reason, can create power law distributions.
Because it arises naturally, changing this distribution would mean forcing hundreds of thousands of bloggers to link to certain blogs and to de-link others, which would require both global oversight and the application of force. Reversing the star system would mean destroying the village in order to save it.
Inequality and Fairness
Given the ubiquity of power law distributions, asking whether there is inequality in the weblog world (or indeed almost any social system) is the wrong question, since the answer will always be yes. The question to ask is "Is the inequality fair?" Four things suggest that the current inequality is mostly fair.
The first, of course, is the freedom in the weblog world in general. It costs nothing to launch a weblog, and there is no vetting process, so the threshold for having a weblog is only infinitesimally larger than the threshold for getting online in the first place.
The second is that blogging is a daily activity. As beloved as Josh Marshall (TalkingPointsMemo.com) or Mark Pilgrim (DiveIntoMark.org) are, they would disappear if they stopped writing, or even cut back significantly. Blogs are not a good place to rest on your laurels.
Third, the stars exist not because of some cliquish preference for one another, but because of the preference of hundreds of others pointing to them. Their popularity is a result of the kind of distributed approval it would be hard to fake.
Finally, there is no real A-list, because there is no discontinuity. Though explanations of power laws (including the ones here) often focus on numbers like "12% of blogs account for 50% of the links", these are arbitrary markers. The largest step function in a power law is between the #1 and #2 positions, by definition. There is no A-list that is qualitatively different from their nearest neighbors, so any line separating more and less trafficked blogs is arbitrary.
The Median Cannot Hold
However, though the inequality is mostly fair now, the system is still young. Once a power law distribution exists, it can take on a certain amount of homeostasis, the tendency of a system to retain its form even against external pressures. Is the weblog world such a system? Are there people who are as talented or deserving as the current stars, but who are not getting anything like the traffic? Doubtless. Will this problem get worse in the future? Yes.
Though there are more new bloggers and more new readers every day, most of the new readers are adding to the traffic of the top few blogs, while most new blogs are getting below average traffic, a gap that will grow as the weblog world does. It's not impossible to launch a good new blog and become widely read, but it's harder than it was last year, and it will be harder still next year. At some point (probably one we've already passed), weblog technology will be seen as a platform for so many forms of publishing, filtering, aggregation, and syndication that blogging will stop referring to any particularly coherent activity. The term 'blog' will fall into the middle distance, as 'home page' and 'portal' have, words that used to mean some concrete thing, but which were stretched by use past the point of meaning. This will happen when head and tail of the power law distribution become so different that we can't think of J. Random Blogger and Glenn Reynolds of Instapundit as doing the same thing.
At the head will be webloggers who join the mainstream media (a phrase which seems to mean "media we've gotten used to.") The transformation here is simple - as a blogger's audience grows large, more people read her work than she can possibly read, she can't link to everyone who wants her attention, and she can't answer all her incoming mail or follow up to the comments on her site. The result of these pressures is that she becomes a broadcast outlet, distributing material without participating in conversations about it.
Meanwhile, the long tail of weblogs with few readers will become conversational. In a world where most bloggers get below average traffic, audience size can't be the only metric for success. LiveJournal had this figured out years ago, by assuming that people would be writing for their friends, rather than some impersonal audience. Publishing an essay and having 3 random people read it is a recipe for disappointment, but publishing an account of your Saturday night and having your 3 closest friends read it feels like a conversation, especially if they follow up with their own accounts. LiveJournal has an edge on most other blogging platforms because it can keep far better track of friend and group relationships, but the rise of general blog tools like Trackback may enable this conversational mode for most blogs.
In between blogs-as-mainstream-media and blogs-as-dinner-conversation will be Blogging Classic, blogs published by one or a few people, for a moderately-sized audience, with whom the authors have a relatively engaged relationship. Because of the continuing growth of the weblog world, more blogs in the future will follow this pattern than today. However, these blogs will be in the minority for both traffic (dwarfed by the mainstream media blogs) and overall number of blogs (outnumbered by the conversational blogs.)
Inequality occurs in large and unconstrained social systems for the same reasons stop-and-go traffic occurs on busy roads, not because it is anyone's goal, but because it is a reliable property that emerges from the normal functioning of the system. The relatively egalitarian distribution of readers in the early years had nothing to do with the nature of weblogs or webloggers. There just weren't enough blogs to have really unequal distributions. Now there are.
Addendum:
David Sifry, creator of the Technorati.com, has created the Technorati Interesting Newcomers List, in part spurred by this article. The list is designed to flag people with low overall link numbers, but who have done something to merit a sharp increase in links, as a way of making the system more dynamic.
| First published February 8, 2003 on the 'Networks, Economics, and Culture' mailing list. Subscribe to the mailing list. |
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Monday, February 17, 2003 |
| Weblogs and power laws Many systems and phenomena are distributed according to a power law distribution. A power law applies to a system when large is rare and small is common. The distribution of individual wealth is a good example of this: there are a very few rich men and lots & lots of poor folks. A familiar way to think about power laws is the 80/20 rule: 80% of the wealth is controlled by 20% of the population. It's been shown that the distribution of links on the web scales according to a power law, so it comes as no surprise that the distribution of links to weblogs does as well. Taking the top 100 most linked to weblogs on Technorati as a data set (specifically from 1/24/03), I used Excel to plot and fit a curve to the data:
.... But what are weblogs competing for? Matt Webb posits that power laws arise due to scarcity.... The scarcity of people's time results in the distribution of links that can be described using power laws. y = 5989.8x^(-0.8309) where y is the # of inbound blogs and x is the rank of the site. I plotted the top 100 data again and tried to fit three curves to it:
The dotted blue line is a linear equation, the dashed red line is a quadratic equation, and the solid black line is the aforementioned power law equation. As you can see, the linear and quadratic equations fit the data poorly. The R-squared for the linear equation is 0.31, 0.55 for the quadratic, and 0.99 for the power law equation. So the quadratic is an improvement over the linear equation, but neither compare to the excellent fit of the power law and the excellent results that would follow from using it for Technorati's interesting recent blogs lists. 11:58:17 PM |
| Breaking the (power) law I thought about the problem that this presented to a traditional link engine. When you rank bloggers simply by the number of people who link to them, you get a very static list of "a-list" bloggers, as shown by the Technorati Top 100. What I wanted to do was to break that power law, and give more exposure to the lesser known, but still interesting bloggers, especially on days when they stand out and do something interesting. Basically, the idea is that for a relatively obscure blogger who has, say, 40 people currently linking to his blog, getting 4 or 5 new blogs linking to him can have the same effect as a a-list blogger getting 40 or 50 new links. This is interesting research for me, but the most satisfying thing about it is that I've found a way to identify interesting new writers and add them to my blogroll. 11:46:58 PM |
a detailed analysis of Power laws as applied to Weblogs, Newspapers and Movies: http://homepage.mac.com/kevinmarks/powerlaws.html The conclusions he comes to are: 1. Weblog links do follow a power law [Kevin Marks] 11:26:34 PM |
... Investigating the "blogosphere" is interesting, but not nearly as interesting as recognizing that there are blogospheres. And these spheres are neither wholly seperate nor wholly integrated with the rest of the network. What constitutes a border for such a sphere? What does this differentiation mean to the structure of the whole. The author, Alexander Halavais, works at School of Infomatics at U. Buffalo. Either we're brining him in for a student speakers talk or I'm gonna go visit him. Or both. |
... Although the search engines and metaindexes are useful, they are no longer the first place you go. I read my RSS news feeds before I go searching on a portal for news. As Dave says, don't know most of the blogs on the top 100 list and I don't care. We are organized into more intelligent communities and although there is a power law of sorts with respect to blogs that get a lot of attention, there are many local peaks. I think it looks much more like clusters of blogs with interconnections between communities. A lot like a strength of weak ties sort of map.
...
Technorati top 100 ranking is not as important to me as WHO is linking to me. When I was running Infoseek, all I cared about was HOW MANY pages views we were getting. Sure I brag about my page views to people who don't blog because that's a metric they understand, but the really interesting stuff is going on at a higher level I think.
So... How do we capture the next higher level of order? Well, that's what I hoped you might have an answer for. I think there are ways to look at this subjectively.
One way might be to track a meme through blogspace. See how an idea like your article gets picked up, quoted and where it ends up. Map that and you have one space. Each meme is like a tracer. Some communities will pick up certain ideas, while other will not. You can find the weak ties between to communities as these memes make their way across networks. MANY memes will end up being very local, and SOME will end up on EVERY blog. But I don't know how to do this.
I also want to read his paper on the connection between weblogs, power laws, and democracy.
[Joi Ito]
My post on Distribution of Choice was a little long winded, so let me sum up:
| Network | Size | Description | Distribution |
| Political Network | ~1000s | Blogs as mass media | Power-law (scale-free) |
| Social Network | ~150 | Blogging Classic | Bell-curve (random) |
| Creative Network | ~12 | Blogs as dinner conversation | Dense (equal) |
A link to a site you read isnt the same as a link to someone you know through their blog or someone you actively collaborate with.
After reviewing data of work relationships, information flows and knowledge exchanges from hundreds of consulting assignments inside Fortune 2000 organizations Valdis Krebs did not see much evidence of power laws in this data. His data is of confirmed ties [both persons agreed/recognized their mutual interactions/flows/relationships] from a worldwide pool of clients dating back to 1988. Of course he found some people were better connected than others, but the extreme hubs found in power law networks just were not evident.
Adapting a famous line from the movie "Blazing Saddles" Valdis concluded: "Power Law? There ain't no stinkin' power law in this data!"
This conclusion fits well with Duncan Watts observation that the more you ratchet up the requirements for a link, recognized connections diminish, and the less you see power laws.
Which makes all the noise about Power-laws off target. I had the pleasure of having a dinner conversation with Clay last night. Yes, he should start a weblog, but he has his own reasons for not doing so yet, which I'll let him explain for himself. But studying the structure of the weblog ecosystem does not have to be an anthropological exercise. Its a wonderful testament to the energy of blogspace that Dave Sifry created a new index to reveal the neglected tail of the Power-law distribution of a Political Network. But we don't have to screw the Power-law or use statistical techniques to reveal a different distribution. This approach has tremendous value in allowing new cream to arise to the top. Both innovations are still attempting to filter the wrong set of data and to generalize all of blogspace. What matters isnt breaking these laws, but the perspective that weblogs, aside from the Political Network publishing dynamics, are communication tools for group forming in Social Networks and Creative Networks. Meg asks the right question: what if these tools can expand our capacities? What if 12 and 150 become averages instead of limits?
Other people are thinking in similar terms from an anthropological perspective as participants. The Social and Creative Networks are where the new and valuable interpersonal connections are being made.
In the coming days I will build upon the Network Ecosystem Model to explain the Distribution of Influence and Distribution of Social Capital. My head hurts, but this is getting interesting.
[Ross Mayfield's Weblog]
