Minding the Planet

My Burma Meme Spreads to 17,000 Web Pages in just one week!

I've been tracking the progress of my Burma protest meme. In just under one week it has spread to almost 17,000 web pages and it continues to grow. (For the latest number, click here). It's great to see the blogosphere pick this up, and I'm glad to be able to do something to help raise awareness of this important human rights issue.

This meme is also an example of an interesting new way to spread content on the Web -- whether for a protest or an ad or any other kind of announcement. It's kind of like a chain letter, but via weblogs. There are many different ways to structure these memes with varying levels of virality and benefit to participants. For some earlier work I've done on meme propagation on the Web see my GoMeme experiments from a few years ago. In those experiments I created a series of memes that spread widely through the blogosphere, based on different viral messages, surveys, and benefits to participants. Other people then tracked the statistics of the memes as they spread. It turned out to be a very interesting study of superdistribution of content along social networks.

Networked Genome -- New Finding Shatters Current Thinking

A new finding has discovered that the human genome may be highly networked. That is, genes do not operate in isolation, but rather they are networked together in a far more complex ecosystem than previously thought. It may be impossible to separate one gene from another in fact. This throws into question not only our understanding of genetics and the human genome, but also the whole genomics industry, which relies heavily on the idea that genes and drugs based on them can be patented:

The principle that gave rise to the biotech industry promised benefits that were equally compelling. Known as the Central Dogma of molecular biology, it stated that each gene in living organisms, from humans to bacteria, carries the information needed to construct one protein.

The scientists who invented recombinant DNA in 1973 built their innovation on this mechanistic, "one gene, one protein" principle.

Because donor genes could be associated with specific functions, with discrete properties and clear boundaries, scientists then believed that a gene from any organism could fit neatly and predictably into a larger design - one that products and companies could be built around, and that could be protected by intellectual-property laws.

This presumption, now disputed, is what one molecular biologist calls "the industrial gene."

"The industrial gene is one that can be defined, owned, tracked, proven acceptably safe, proven to have uniform effect, sold and recalled," said Jack Heinemann, a professor of molecular biology in the School of Biological Sciences at the University of Canterbury in New Zealand and director of its Center for Integrated Research in Biosafety.

In the United States, the Patent and Trademark Office allows genes to be patented on the basis of this uniform effect or function. In fact, it defines a gene in these terms, as an ordered sequence of DNA "that encodes a specific functional product."

In 2005, a study showed that more than 4,000 human genes had already been patented in the United States alone. And this is but a small fraction of the total number of patented plant, animal and microbial genes.

In the context of the consortium's findings, this definition now raises some fundamental questions about the defensibility of those patents.

If genes are only one component of how a genome functions, for example, will infringement claims be subject to dispute when another crucial component of the network is claimed by someone else?

Might owners of gene patents also find themselves liable for unintended collateral damage caused by the network effects of the genes they own?

And, just as important, will these not-yet-understood components of gene function tarnish the appeal of the market for biotech investors, who prefer their intellectual property claims to be unambiguous and indisputable?

While no one has yet challenged the legal basis for gene patents, the biotech industry itself has long since acknowledged the science behind the question.

"The genome is enormously complex, and the only thing we can say about it with certainty is how much more we have left to learn," wrote Barbara Caulfield, executive vice president and general counsel at the biotech pioneer Affymetrix, in a 2002 article on Law.com called "Why We Hate Gene Patents."

"We're learning that many diseases are caused not by the action of single genes, but by the interplay among multiple genes," Caulfield said. She noted that just before she wrote her article, "scientists announced that they had decoded the genetic structures of one of the most virulent forms of malaria and that it may involve interactions among as many as 500 genes."

Even more important than patent laws are safety issues raised by the consortium's findings. Evidence of a networked genome shatters the scientific basis for virtually every official risk assessment of today's commercial biotech products, from genetically engineered crops to pharmaceuticals.

Read the rest here

Intelligence is in the Connections

Google's Larry Page recently gave a talk to the AAAS about how Google is looking towards a future in which they hope to implement AI on a massive scale. Larry's idea is that intelligence is a function of massive computation, not of "fancy whiteboard algorithms." In other words, in his conception the brain doesn't do anything very sophisticated, it just does a lot of massively parallel number crunching. Each processor and its program is relatively "dumb" but from the combined power of all of them working together "intelligent" behaviors emerge.

Larry's view is, in my opinion, an oversimplification that will not lead to actual AI. It's certainly correct that some activities that we call "intelligent" can be reduced to massively parallel simple array operations. Neural networks have shown that this is possible -- they excel at low level tasks like pattern learning and pattern recognition for example. But neural networks have not proved capable of higher level cognitive tasks like mathematical logic, planning, or reasoning. Neural nets are theoretically computationally equivalent to Turing Machines, but nobody (to my knowledge) has ever succeeded in building a neural net that can in practice even do what a typical PC can do today -- which is still a long way short of true AI!

Somehow our brains are capable of basic computation, pattern detection and learning, simple reasoning, and advanced cognitive processes like innovation and creativity, and more. I don't think that this richness is reducible to massively parallel supercomputing, or even a vast neural net architecture. The software -- the higher level cognitive algorithms and heuristics that the brain "runs" -- also matter. Some of these may be hard-coded into the brain itself, while others may evolve by trial-and-error, or be programmed or taught to it socially through the process of education (which takes many years at the least).

Larry's view is attractive but decades of neuroscience and cognitive science have shown conclusively that the brain is not nearly as simple as we would like it to be. In fact the human brain is far more sophisticated than any computer we know of today, even though we can think of it in simple terms. It's a highly sophisticated system comprised of simple parts -- and actually, the jury is still out on exactly how simple the parts really are -- much of the computation in the brain may be sub-neuronal, meaning that the brain may actually a much much more complex system than we think.

Perhaps the Web as a whole is the closest analogue we have today for the brain -- with millions of nodes and connections. But today the Web is still quite a bit smaller and simpler than a human brain. The brain is also highly decentralized and it is doubtful than any centralized service could truly match its capabilities. We're not talking about a few hundred thousand linux boxes -- we're talking about hundreds of billions of parallel distributed computing elements to model all the neurons in a brain, and this number gets into the trillions if we want to model all the connections. The Web is not this big, and neither is Google.

'Bemes' are Defining the Blogosphere

Tom Hayes has an interesting post in which he coins the word 'beme" to mean a meme that spreads in the blogosphere.

Michael Malone's ABC News column on Thursday mentioning "bemes" has certainly produced a lot of interest.  Originally, I coined the word beme to describe a meme propagated by blogs and bloggers.  Now I can see that the turn of phrase has a much bigger potential to capture the rapidly-moving cultural touchstones of the Bubble Generation.

As you may know, "meme" was first defined by Richard Dawkins in 1976 as "a unit of cultural information" spread from one mind to another. In other words, a viral idea that eventually becomes common knowledge.

Fast forward three decades, and it seems to me that technology has turbo-charged the meme process.  Looking for the juste mot to describe a "purposeful" meme fed into the vast human network of the Internet, either by blog, email, video, phonecast, social media or other viral means, beme seems to fit the bill. 

A beme is a turbo-charged meme made possible entirely by the existence of the network affect.  A beme can be impactful because it is lurid--a photo of a panty-less Britney Spears, or humorous--a whimisical video of the band OKGO on treadmills, or gut-wrenching--the sad tirade by comedian Michael Richards.  A beme can cement an idea with the public in a way that cannot be legislated or regulated.  No legal effort by Cisco to enforce a trademark, for example, will make the public unlearn that Apple produces the iPhone.

• A meme is old media, a beme is new media.
• A meme takes off by accident, a beme by design.
• A meme can take years to surface, a beme hours.

Interesting Idea: Start a Magazine that is a Wiki

I was reading this article in Wired magazine about wikis, where the article itself is a wiki that the readers can contribute to -- and an idea occurred to me. What if you could make an entire magazine that was in a fact a wiki? This magazine would be published online via a Website running a wiki engine. Every issue would be by and for the community of readers. There would be an editorial group among the readers that would decide what to write articles about for the next issue of the magazine, and then the community would work to write the articles. To get into the editorial group, remain there, and have a vote as an editor, a community member would have to make a certain number of (non-spurrious) contributions to articles on an ongoing basis (and/or maintain a certain reputation in the community as measured in some other manner).

I can imagine this idea taking off and a lot of these "wikazines" forming around various subject areas. It makes sense that communities of people who are interested in subjects could help to research and write about them. Of course in such communities there would be some people who put more effort in than others, and some who were more like readers or lurkers. But it would still be much more involving than old "one-way media."

In some ways communities like Digg simulate this -- people essentially vote on what is interesting and this filters up to become the featured content on the site. But that is still one step removed from the creative process itself -- only the readers participate, not the content authors. What's interesting about this proposal is that it blurs the distinction between an author and a reader, and provides a way for a magazine to be truly emergent and community-driven. OK, I'm too busy to start this, but I hope someone out there on the lazyweb takes this idea and runs with it. Please let me know if you find examples of this.

Radar Networks is Seeking Search Engineers for Large-Scale Web Mining Initiative

My company, Radar Networks, is building a very large dataset by crawling and mining the Web. We then apply a range of new algorithms to the data (part of our secret sauce) to generate some very interesting and useful new information about the Web. We are looking for a few experienced search engineers to join our team -- specifically people with hands-on experience designing and building large-scale, high-performance Web crawling and text-mining systems. If you are interested, or you know anyone who is interested or might be qualified for this, please send them our way. This is your chance to help architect and build a really large and potentially important new system. You can read more specifics abour our open jobs here.

I'm Going to Start Blogging About Radar Networks Here

I haven't blogged very much about my stealth startup, Radar Networks, yet. At the most, I've made a few cryptic posts and announcements in the past, but we've been keeping things pretty quiet. That's been a conscious  decision because we have been working intensively on R&D  and we just weren't ready to say much yet.

Unlike some companies which have done massive and deliberate hype about unreleased vapor software, we really felt it would be better to just focus on our work and let it speak for itself when we release it.

The fact is we have been working quietly for several years on something really big, and really hard. It hasn't always been easy -- there have been some  technical challenges that took a long time to overcome. And it took us a long time to find VC's daring enough to back us.

The thing is, what we are making is not a typical Web 2.0 "build it and flip it in 6 months" kind of project. It's deep technology that has long-term infrastructure-level implications for the Web and the future of content. And until recently we really didn't even have a good way to describe it to non-techies. So we just focused on our work and figured we would talk about it someday in the future.

But perhaps I've erred on the side of caution -- being so averse to gratuitous hype that I have literally said almost nothing publicly about the company. We didn't even issue a press release about our Series A round (which happened last April -- I'll be adding one to our new corporate site, which launches on Sunday night however, for historical purposes), and until today, our site at Radar has been  just a one-page placeholder with no info at all about what we are doing.

But something happened that changed my mind about this recently. I had lunch with my friend Munjal Shah, the CEO of Riya. Listening to Munjal tell his stories about how he has blogged so openly about Riya's growth, even from way before their launch, and how that has provided him and his team with amazingly valuable community feedback, support, critiques, and new ideas, really got me thinking. Maybe it's time Radar Networks started telling a little more of its story? It seems like the team at Riya really benefitted from being so open. So although, we're still in stealth-mode and there are limits to what we can say at this point, I do think there are some aspects we can start to talk about, even before we've launched. And besides that our story itself is interesting -- it's the story of what it's like to build and work in a deep-technology play in today's venture economy.

So that's what I'm going to start doing here -- I'm going to start telling our story on this blog, Minding the Planet. I already have around 500 regular readers, and most of them are scientists and hard-core techies and entrepreneurs. I've been writing mainly about emerging technologies that are interesting enough to inspire me to post about them, and once in a while about ideas I have been thinking about. These are also subjects that are of interest to the people who read this blog. But now I'm also going to start blogging more about Radar Networks and what we are doing and how it's going. I'll post about our progress, the questions we have, the achievements on our team, and of course news about our launch plans. And I hope to hear from people out there who are interested in joining us when we do our private invite-only beta tests.

We're still quite a ways from a public launch, but we do have something working in the lab and it's very exciting. Our VC's want us to launch it now, but it's still an early alpha and we think it needs a lot more work (and testing) before our baby is ready to step out into the big world out there. But it looks promising. I do think, all modesty aside for a moment, that it has the potential to really advance the Web on a broad scale. And it's exciting to work on.

This post is already long enough, so I'll finish here for the moment. In my upcoming posts I will start to talk a little bit more about the new category that Radar Networks is going to define, and some of the technologies we're using, and challenges we've overcome along the way. And I'll share some insights, and stories, and successes we've had.

But I'm getting ahead of myself, and besides that, my dinner's ready. More later.

Harnessing The Collective Mind

Today I read an interesting article in the New York Times about a company called Rite-Solutions which is using a home-grown stock market for ideas to catalyze bottom-up innovation across all levels of personnel in their organization. This is a way to very effectively harness and focus the collective creativity and energy in an organization around the best ideas that the organization generates.

Using virtual stock market systems to measure community sentiment is not a new concept but it is a new frontier. I don't think we've even scratched the surface of what this paradigm can accomplish. For lots of detailed links to resources on this topic see the wikipedia entry on prediction markets. This prediction markets portal also has collected interesting links on the topic. Here is an informative blog post about recent prediction market attempts. Here is a scathing critique of some prediction markets.

There are many interesting examples of prediction markets on the Web:

• Google uses a similar kind of system -- their own version of a prediction market -- to enable staff members to collaboratively predict the likelihood that various internal projects and events will occur on-schedule.
• Yahoo also has a prediction market called BuzzGame that enables visitors to help predict technology trends. 
• Newsfutures Exchange is a prediction market about the news, which is powered by a commercial prediction market engine sold by a company called Newsfutures.
• BlogShares, a fantasy stock market for Weblogs in which players invest virtual money in the blogs they think will gain the most audience share.
• Intrade is another exchange for trading on idea futures.
• The Iowa Political Futures Exchange is a prediction market that focuses on political change.
• Tradesports is a prediction market around sports topics.
• The Hollywood Stock Exchange is a prediction market around movies.
• The Foresight Exchange is another prediction market for predicting future events.

Here are some interesting, more detailed discussions of prediction market ideas and potential features.

• http://hanson.gmu.edu/ideafutures.html
• http://hanson.gmu.edu/ifwired.html
• http://ideastockexchange.com/about.htm

Another area that is related, but highly underleveraged today, are ways to enable communities to help establish whether various ideas are correct using argumentation. By enabling masses of people to provide reasons to agree or disagree with ideas, and with those reasons as well, we can automatically rate what ideas are most agreed with or disagreed with. One very interesting example of this is TruthMapping.com. Some further concepts related to this approach are discussed in this thread.

Big Thinkers' Most Dangerous Ideas

The Edge has published mini-essays by 119 "big thinkers" on their "most dangerous ideas" -- fun reading.

The history of science is replete with discoveries that were considered socially, morally, or emotionally dangerous in their time; the Copernican and Darwinian revolutions are the most obvious. What is your dangerous idea? An idea you think about (not necessarily one you originated) that is dangerous not because it is assumed to be false, but because it might be true?

 

A Cool Thingy...

This is cool Click to see why.  I think this idea has great value for viral, meme-based Web advertising. Just imagine: Advertisers could release really cool animations to add to sites, and site owners could add them into their sites for entertainment or humor. The animations could run ads within them as well. It's fun. Everyone wins, everyone's happy. And of course users can aim these animations at any other site so visitors who like it can spread it to their own sites. Very smart!!! Very Web 2.0.

Folktologies -- Beyond the Folksonomy vs. Ontology Distinction

First of all I know Clay Shirky, and he's a good fellow. But he's simply wrong about his claim that "tagging" (of the flavor that is appearing on del.icio.us -- what I call "social tagging") is inherently better than the use of formal ontologies. Clay favors the tagging approach because it is bottom-up and emergent in nature, and he argues against ontologies because pre-specification cannot anticipate the future. But this is a simplistic view of both approaches. One could just as easily argue against tagging systems because they don't anticipate the future -- they are shortsighted, now-oriented systems that fail to capture the "big picture" or to optimally organize resources for the long-term. Their saving grace is that over time they do (hopefully) self-organize and prune out the chaff, but that depends both on the level of participation and the quality of that participation.

A Stock Market for Ideas

Media Mammon  is a new stock market for memes. You can invest play money in words and phrases that are spreading through the media. May the best meme win! See also: A Physics of Ideas.

My "A Physics of Ideas" Manifesto has been Published!

Change This, a project that helps to promote interesting new ideas so that they get noticed above the noise level of our culture has published my article on "A Physics of Ideas" as one of their featured Manifestos. They use an innovative PDF layout for easier reading, and they also provide a means for readers to provide feedback and even measure the popularity of various Manifestos. I'm happy this paper is getting noticed finally -- I do think the ideas within it have potential. Take a look.

A Blog Novel

Rohit Gupta, a Bombay-based writer, who also reads this blog, is writing a blog-novel. He has come up with an innovative way to promote it -- by letting readers choose quotes from his text to "own" -- by choosing a quote and linking to his blog-novel from it, he will in return link back to your blog from that quote in his novel. It's similar to my earlier GoMeme experiments, except in this case his novel is the meme that is spreading via a cooperative linking incentive.

Good idea, Rohit! I choose this quote from your novel:

"The other article, an interesting one, is a 2000-word piece on the history of mathematical heretics known as the Circlesquarers, and the transcendental nature of the number Π."

Great Article on Psychohistory and Sociophysics -- Can We Predict Behavior?

Great find from Rob Usey at Psydex Corporation: This article is a survey of the emerging field of "sociophysics" which attempts to apply statistical mechanics to predict human social behavior. It's very cool stuff if you're interested in social networks, memes, sociology and prediction science. The article discusses recent progress towards Isaac Asimov's vision for a science of Psychohistory as proposed in his Foundation stories. This relates in many ways to my previous article on "A Physics of Ideas" in which I proposed some elementary ways to measure the trajectories of memes as if they were moving particles in a Newtonian system.

Detailed Analysis of GoMeme 1.0 Results

Greg Tyrell, a PhD student with a strong interest in bioinformatics, has put together a detailed analysis and report on the GoMeme 1.0 experiment, containing several visualizations and results of the survey. Nice work Greg!

Also in other news, Google has started indexing the results. Currently there are 733 results when searching for sites with original, super-long GUID. There are 867 results when searching for the unique string "To add your blog to this experiment, copy this entire posting to your blog, and fill out the info below, substituting your own information in your posting, where appropriate" which was in the instructions -- this number should include sites that did not put the whole GUID in. Technorati, which seems to be working better today, finds 58 sites with the long GUID, and none for the instructions text above. So I guess Google wins so far. But I am glad that Technorati is starting to get their bugs fixed! I noticed that blog stats are starting to be updated again.

I also got an interesting link to another Meme visualization, which although having nothing to do with our experiment as far as I can tell, is a nice concept. It takes forever to build out the full visualization and the tree appears to be almost white on my white background making it hard to see, but still worth a look -- Meme Tree

Change This

I am helping Change This, a project to spread manifestos on new ideas by key thinkers. They have asked me to help host one of their manifestos, Creating Customer Evangelists. You can also download it directly from

August 16, 2004 in Business, Memes & Memetics | Permalink | Comments (5) | TrackBack (3)

Digg This | Save to del.icio.us

Note: This experiment is now finished.

(GoMeme 3.0 - Note: This is not an ordinary article. We have added some special information at the end. Read this entire article, and then follow the instructions at the end to pass it on in a new way...)

Note: This experiment is now finished.

GoMeme 2.0 -- Copy This GoMeme From This Line to The End of this article, and paste into your blog. Then follow the instructions below to fill it out for your site.

Steal This Post!!!! This is a GoMeme-- a new way to spread an idea along social networks. This is the second generation meme in our experiment in spreading ideas. To find out what a GoMeme is, and how this experiment works, or just to see how this GoMeme is growing and discuss it with others, visit the Root Posting and FAQ for this GoMeme at www.mindingtheplanet.net .

I wonder if anyone from MoveOn.Org or the Republicans will notice our GoMeme experiments? (Not that I'm taking sides -- I'll simply be happy if somebody wins the election!) Grassroots political campaigns could potentially really benefit from the techniques we're testing here. For example, imagine a "blog meme" for a political campaign -- a meme that states some useful facts about a candidate and their opponent, perhaps has some survey questions and a GUID, and has the added benefit of a cool Improve-Your-Google-Ranking-By-Hosting-This-Meme candy coating? Wow -- it could spread the message to a lot of blogs pretty quickly if done right. That might actually work. But I try to stay out of politics, so I'm not taking sides here or endorsing anyone. If you read this and know the "right people" -- feel free to suggest the idea to them.

This posting is the FAQ and introduction for a new, improved, second-generation meme experiment that is designed to spread faster and more broadly than the first meme experiment. We call this kind of meme a "GoMeme" (pronounced Go-Meem), because it is a meme that is designed to Go. The actual GoMeme, which you can add to your Website is located, here. Before you do this, please read this FAQ so you know how it works.

Matt Poepping has come up with an interesting idea for how to create a fully distributed searchable database on the Net. It's a cool enough idea and approach that people should see his RFC and comment on it. He may be onto something important here.

Here's an idea I've had recently that is related to the Meme Propagation experiment (see posts below on this blog for more about that ongoing experiment). The concept is for a new, meme-based, way to syndicate content across blogs. Here's how it might work:

1. You join a "meme syndication network" by joining at a central site. You get an account where you can profile your blog. You also set your blog's syndication inputs -- a set of other blogs that are also in the network that you are willing to automatically syndicate content from.

2. When you complete this, you are given an automatically generated HTML element containing a script to put in your blog sidebar, or anywhere else in your layout. This script is auto-generated for you from a central site that manages the network. The script automatically displays short excerpts for blog postings (pieces of microcontent) that have been "picked up" by your site from your registered "inputs" in the network. You place this script in your layout.

3. In the area created by the script in your site, you see a listing of blog postings that have been syndicated to your site from your inputs. You can post to your network by going to your account at the central network site and posting (or copying in the URL for anything you want to post) there. Any network-member sites that treat your node in the network as an "input" will then *automatically* pickup your posting and display it on their page.

Meme Update: The Meme is already global and the rate of growth is showing signs of exponential increase. It's made the Daypop top list, also same with Blogdex. It's made its way onto several early-adopter sites and lists. Already the results are interesting. One thing that is clear is that there is quite a lag time in Blogspace: This applies not just to blogs, but also to aggregation sites and search sites -- which don't update nearly as often as one might think.

Comments:

It seems that certain bloggers read and post much more frequently than others -- we could call their blogs "hot zones," to borrow a term from epidemiology.
.

NOTE: This experiment is now finished.

This is an experiment in spreading ideas across weblogs using the principles of viral marketing and social networks using a new method for making content more viral, which we call a "GoMeme."

This animated visualizer lets you enter a word (in the little search box on the bottom left) and then shows the word situated next to other words that are used with similar frequency in English. It's cool -- you can discover some interesting things. Read the about page for more on that. This system would be really good if it used the concepts from my paper on A Physics of Ideas. What they should do is show the words next to other words with similar present momentum. That would be much more informative and useful than simply visualizing words as if all mentions happened at once. The fact that mentions occur over time (and space) is what is really important. It is much more interesting than the mere total number of mentions since time began. I would love to see a visualization of meme momentums as I have proposed in my article above. If you feel like making one, please let me know!

by Nova Spivack
http://www.mindingtheplanet.net

Original: July 8, 2004
Revised: February 5, 2005


(Permission to reprint or share this article is granted, with a citation to this Web Page: http://www.mindingtheplanet.net)

This paper provides an overview of a new approach to measuring the physical properties of ideas as they move in real-time through information spaces and populations such as the Internet. It has applications to information retrieval and search, information filtering, personalization, ad targeting, knowledge discovery and text-mining, knowledge management, user-interface design, market research, trend analysis, intelligence gathering, machine learning, organizational behavior and social and cultural studies.

Introduction

In this article I propose the beginning of what might be called a physics of ideas. My approach is based on applying basic concepts from classical physics to the measurement of ideas -- or what are often called memes -- as they move through information spaces over time.

Ideas are perhaps the single most powerful hidden forces shaping our lives and our world. Human events are really just the results of the complex interactions of myriad ideas across time, space and human minds. To the extent that we can measure ideas as they form and interact, we can gain a deeper understanding of the underlying dynamics of our organizations, markets, communities, nations, and even of ourselves. But the problem is, we are still remarkably primitive when it comes to measuring ideas. We simply don't have the tools yet and so this layer of our world still remains hidden from us.

However, it is becoming increasingly urgent that we develop these tools. With the evolution of computers and the Internet ideas have recently become more influential and powerful than ever before in human history. Not only are they easier to create and consume, but they can now move around the world and interact more quickly, widely and freely. The result of this evolutionary leap is that our information is increasingly out of control and difficult to cope with, resulting in the growing problem of information overload.

There are many approaches to combating information overload, most of which are still quite primitive and place too much burden on humans.  In order to truly solve information overload, I believe that what is ultimately needed is a new physics of ideas -- a new micro-level science that will enable us to empirically detect, measure and track ideas as they develop, interact and change over time and space in real-time, in the real-world.

In the past various thinkers have proposed methods for applying concepts from epidemiology and population biology to the study of how memes spread and evolve across human societies. We might label those past attempts as "macro-memetics" because they are chiefly focused on gaining a macroscopic understanding of how ideas move and evolve. In contrast, the science of ideas that I am proposing in this paper is focused on the micro-scale dynamics of ideas within particular individuals or groups, or within discrete information spaces such as computer desktops and online services and so we might label this new physics of ideas as a form of "micro-memetics."

To begin developing the physics of ideas I believe that we should start by mapping existing methods in classical physics to the realm of ideas. If we can treat ideas as ideal particles in a Newtonian universe then it becomes possible to directly map the wealth of techniques that physicists have developed for analyzing the dynamics of particle systems to the dynamics of idea systems as they operate within and between individuals and groups.

The key to my approach is to empirically measure the meme momentum of each meme that is active in the world. Using these meme momenta we can then compute the document momentum of any document that contain those memes. The momentum of a meme is a measure of the force of that meme within a given space, time period, and set of human minds (a "context"). The momentum of a document is the force of that document within a given context.

Once we are able to measure meme momenta and document momenta we can then filter and compare individual memes or collections of memes, as well as documents or collections of documents, according to their relative importance or "timeliness" in any context.

Using these techniques we can empirically detect the early signs of soon-to-be-important topics, trends or issues; we can measure ideas or documents to determine how important they are at any given time for any given audience; we can track and graph ideas and documents as their relative importances change over time in various contexts; we can even begin to chart the impact that the dynamics of various ideas have on real-world events. These capabilities can be utilized in next-generation systems for knowledge discovery, search and information retrieval, knowledge management, intelligence gathering and analysis, social and cultural research, and many other purposes.

The rest of this paper describes how we might attempt to do this, some applications of these techniques, and a number of further questions for research.

Draft 1.1 for Review (integrates some fixes from readers)
Nova Spivack (www.mindingtheplanet.net)

INTRODUCTION

This article presents some thoughts about the future of intelligence on Earth. In particular, I discuss the similarities between the Internet and the brain, and how I believe the emerging Semantic Web will make this similarity even greater.

DISTRIBUTED INTELLIGENCE

The Semantic Web enables the formal communication of a higher level of language -- metalanguage. Metalanguage is language about language -- language that encodes knowledge about how to interpret and use information. Metalanguages – particularly semantic metalanguages for encoding relationships between information and systems of concepts – enable a new layer of communication and processing. The combination of computing networks with semantic metalanguages represents a major leap in the history of communication and intelligence.

The invention of written language long ago changed the economics of communication by making it possible for information to be represented and shared independently of human minds. This made it less costly to develop and spread ideas widely across populations in space and time. Similarly, the emergence of software based on semantic metalanguages will dramatically change the economics not only of information distribution, but of intelligence -- the act of processing and using information.

Semantic metalanguages provide a way to formally express, distribute and share the knowledge necessary to interpret and use information, independently of the human mind. In other words, they make it possible not just to write down and share information, but also to encode and share the background necessary for intelligently making use of that information. Prior to the invention of such a means to share this background knowledge about information, although information could be written and shared, the recipients of such information had to be intelligent and appropriately knowledgeable in advance in order to understand it. Semantic metalanguages remove this restriction by making it possible to distill the knowledge necessary to understand information into a form that can be shared just as easily as the information itself.

The recipients of information – whether humans or software – no longer have to know in advance (or attempt to deduce) how to interpret and use the information; this knowledge is explicitly coded in the metalanguage about the information. This is important for artificial intelligence because it means that expertise for specific domains does not have to be hard-coded into programs anymore -- instead programs simply need to know how to interpret the metalanguage. By adding semantic metalanguage statements to information data becomes “smarter,” and programs can therefore become “thinner.” Once programs can speak this metalanguage they can easily import and use knowledge about any particular domain, if and when needed, so long as that knowledge is expressed in the metalanguage.

In other words, whereas basic written languages simply make raw information portable, semantic metalanguages make knowledge (conceptual systems) and even intelligence (procedures for processing knowledge) about information portable. They make it possible for knowledge and intelligence to be formally expressed, stored digitally, and shared independently of any particular minds or programs. This radically changes the economics of communicating knowledge and of accessing and training intelligence. It makes it possible for intelligence to be more quickly, easily and broadly distributed across time, space and populations of not only humans but also of software programs.

The emergence of standards for sharing semantic metalanguage statements that encode the meaning of information will catalyze a new era of distributed knowledge and intelligence on the Internet. This will effectively “make the Internet smarter.” Not just monolithic expert systems and complex neural networks, but even simple desktop programs and online software agents will begin to have access to a vast decentralized reserve of knowledge and intelligence.

The externalization, standardization and sharing of knowledge and intelligence in this manner, will make it possible for communities of humans and software agents to collaborate on cognition, not just on information. As this happens and becomes increasingly linked into our daily lives and tools, the "network effect" will deliver increasing returns. While today most of the intelligence on Earth still resides within human brains, In the near future, perhaps even within our lifetimes, the vast majority of intelligence will exist outside of human brains on the Semantic Web.

THE INTERNET IS A BRAIN AND THE WEB IS ITS MIND

Anyone familiar with the architecture and dynamics of the human nervous system cannot help but notice the striking similarity between the brain and the Internet. But is this similarity more than a coincidence - is the Internet really a brain in its own right - the brain of our planet? And is its collective behavior intelligent - does it constitute a global mind? How might this collective form of intelligence compare to that of an individual human mind, or a group of human minds?

I believe that the Internet (the hardware) is already evolving into a distributed global brain, and its ongoing activity (the software, humans and data) represents the cognitive process of an increasingly intelligent global mind. This global mind is not centrally organized or controlled, rather it is a bottom-up, emergent, self-organizing phenomenon formed from flows of trillions of information-processing events comprised of billions of independent information processors.

As with other types of emergent computing systems, for example John Conway’s familiar cellular automaton “The Game of Life,” on the Internet large scale homeostatic systems and seemingly intentional or guided information processes naturally emerge and interact within it. The emergence of sophisticated information systems does not require top-down design or control, it can happen in an evolutionary bottom-up manner as well.

Like a human brain, the Internet is a vast distributed computing network comprised of billions of interacting parallel processors. These processors include individual human beings as well as software programs, and systems of them such as organizations, which can all be referred to as "agents" in this system. Just as the computational power of the human brain as a whole is vastly greater than that of any of the individual neurons or systems within it, the computational power of the Internet is vastly beyond any of the individual agents it contains. Just as the human brain is not merely the sum of its parts, the Internet is more than the sum of its parts - like other types of distributed emergent computing systems, it benefits from the network effect. The power of the system grows exponentially as agents and connections between them are added.

The human brain is enabled by an infrastructure comprised of networks of organic neurons, dendrites, synapses and protocols for processing chemical and electrical messages. The Internet is enabled by an infrastructure of synthetic computers, communications networks, interfaces, and protocols for processing digital information structures. The Internet also interfaces with organic components however – the human beings who are connected to it. In that sense the Internet is not merely an inorganic system – it could not function without help from humans, for the moment at least. The Internet may not be organized in exactly the same form as the human brain, but it is at least safe to say it is an extension of it.

The brain provides a memory system for storing, locating and recalling information. The Internet also provides shared address spaces and protocols for using them. This enables agents to participate in collaborative cognition in a completely decentralized manner. It also provides a standardized shared environment in which information may be stored, addressed and retrieved by any agent of the system. This shared information space functions as the collective memory of the global mind.

Just as no individual neuron in the human brain could be said to have the same form or degree of intelligence as the brain as-a-whole - we individual humans cannot possibly comprehend the distributed intelligence that is evolving on the Internet. But we are part of it nonetheless, whether we know it or not.  The global mind is emerging all around us, and via us, is our creation but it is already becoming independent of us - truly it represents the evolution of a new form of meta-level intelligence that has never before existed on our planet.

Although we created it, the Internet is already far beyond our control or comprehension - it surrounds us and penetrates our world - it is inside our buildings, our tools, our vehicles, and it connects us together and modulates our interactions. As this process continues and the human body and biology begins to be networked into this system we will literally become part of this network - it will become an extension of our nervous systems and eventually, via brain-computer interfaces, it will be an extension of our senses and our minds. Eventually the distinction between humans and machines, and the individual and the collective, will gradually start to dissolve, along with the distinction between human and artificial forms of intelligence.

The Memecodes Project starts with randomly generated Web pages and evolves them to get more search results from Google. Brilliant idea. The only problem is that Google indexing isn't frequent enough, making this process take a bit of time. Still, I think this is a very interesting new approach that could even be a useful utility for sites in general someday.

Notes:

Many people have requested this graph and so I am posting my latest version of it. The Metaweb is the coming "intelligent Web" that is evolving from the convergence of the Web, Social Software and the Semantic Web. The Metaweb is starting to emerge as we shift from a Web focused on information to a Web focused on relationships between things --- what I call "The Relationship Web" or the "Relationship Revolution."

We see early signs of this shift to a Web of relationships in the sudden growth of social networking systems. As the semantics of these relationships continue to evolve the richness of the "arcs" will begin to rival that of the "nodes" that make up the network.

This is similar to the human brain -- individual neurons are not particularly important or effective on their own, rather it is the vast networks of relationships that connect them that encode knowledge and ultimately enable intelligence. And like the human brain, in the future Metaweb, technologies will emerge to enable the equivalent of "spreading activation" to propagate across the network of nodes and arcs. This will provide a means of automatically growing links, weighting links, making recommendations, and learning across distributed graphs of nodes and links. This may resemble a sort of "Hebbian learning" across the link structure of the network -- enhancing the strength of frequently used connections and dampening less used links, and even growing new transitive links when appropriate.

As the intelligence with which such processes unfolds, in a totally decentralized and grassroots manner, we will begin to see signs of emergent "transhuman" intelligences on the network. Web services are the beginning of this -- but imagine if they were connected to autonomous intelligent agents, roaming the network and able to interact with one another, Web sites, and even people. These next-layer intelligences will begin to function as brokers, associators, editors, publishers, recommenders, advertisers, researchers, defenders, buyers, sellers, monitors, aggregators, distributors, integrators, translators, and also as knowledge-stewards responsible for constantly improving the structure and quality of subsets of the Web that they oversee. And while many of these agents will be able to interact intelligently with humans, not all of them will -- most will probably just have interfaces for interacting with other agents.

Vast systems of "hybrid intelligence" (humans + intelligent software) will form -- for example, next-generation communities that intelligently self-organize around emerging topics and trends, smart marketplaces that self-optimize to reduce the cost of transactions for their participants, 'group minds' and 'enterprise minds' that embody and manage the collective cognitiion of teams and organizations, and knowledge networks that function to enable distributed collective intelligence among networks of indivdiuals, across communities and business-relationships.

As the network becomes increasingly autonomous and self-organizing we may say that the network-as-a-whole is becoming "intelligent." But it will be several steps beyond that before it finally "wakes up" -- when the various processes of the network reach that point at which the entire system truly functions as a coordinated, self-aware intelligence. This will require the formation of many higher layers of intelligence -- leading to something that functions like the cerebral cortex in humans. It will also require something that functions as its virtual "self-awareness" -- an internal process of meta-level self-representation, self-projection, self-feedback, self-analysis and self-improvement within the network. For a map of how this may actually unfold over time we might look at the evolutionary history of nervous systems on Earth.

As structures that provide virtual higher-order cognition and self-awareness to the network emerge, connect to one another, and gain sophistication, the Global Brain will self-organize into a Global Mind -- the intelligence of the whole will begin to outpace the intelligence of any of its parts and thus it will cross the threshold from being just a "bunch of interacting parts" to "a new higher-order whole" in its own right -- a global intelligent Metaweb for our planet.

One of the big changes that will be enabled by the coming Metaweb is the shift from application-centric computing to data-centric computing. As the Metaweb evolves, information will be imbued with increasingly sophisticated metadata. HTML provides metadata about formatting and links. XML provides metadata about structure and behavior. RDF, RDFS and OWL provide metadata about relationships and meaning.

As higher levels of metadata are adopted and added to content, the content becomes "smarter" -- more information about how to display, use and interpret the content is added to the content itself. The key here is that this metadata is added in an application-independent manner. In other words, the "intelligence" for interpreting the data is moved out of applications and into the data itself. Thus we move from "smart applications, dumb data" to "smart applications, smart data."

A data-centric world will be very different from the application-centric world of today -- for one thing, application providers will lose much of their competitive advantages (from platform lock-in and closed formats) as data becomes increasingly portable across various tools. Another big change will be in how we think about content -- rather than content being thought of as static documents, every piece of content will be more like an object with its own unique identity and behaviors on the network.

Instead of moving data around we will access these semantic data objects using Web services protocols and interact with them from anywhere like mini-online services. To edit a document we might send commands to an object that represents the document on the network, rather than actually downloading and modifying a local file.

Ultimately this will bring about a shift from desktop computing to network computing -- software will truly become a service and the business model of software will shift to be more like online service business models -- based on subscriptions, a la carte pay-per-use features, and perhaps even advertising. Data objects will be accessible from everywhere and will be responsible for maintaining their own state, relationships and contents, as well as managing their own access, rights and usage policies. These are some of the changes that will come about as the Metaweb evolves.

This diagram (click to see larger version) illustrates why I believe technology evolution is moving towards what I call the Metaweb. The Metaweb is emerging from the convergence of the Web, Social Software and the Semantic Web.

This article discusses new research in how the brain makes buying decisions and other choices -- what is now called "neuromarketing". Neuromarketing researchers seek to discover, and influence, the neurological forces at work inside the mind of potential customers. According to the article, most decisions are made subconsciously and are not necessarily rational at all - in fact they may be primarily governed by emotions and other more subtle cognitive factors such as identity and sense of self. For example, when studied under a functional MRI, the reward centers of brains of subjects who were given "The Pepsi Challenge" lit up when they tasted Pepsi, but Coke actually lit up the parts of the brain responsible for "sense of self" -- a much deeper response. In other words, the Coke brand is somehow connected to deeper neurological structures than Pepsi.

Neuromarketing is interesting -- it's actually something I've been thinking about on my own in an entirely different context. What I am interested in is the question of "What makes people decide that a given meme is 'hot'?" Each of us is immersed in a sea of memes -- we are literally bombarded with thousands or even millions of ideas, brands, products and other news every day -- But how do we decide which ones are "important," "cool," and "hot?" What causes the human brain to pick out certain of these memes at the expense of the others? In other words, how do we differentiate signal from noise, and how do we rank memetic signals in terms of their relative "importance?" Below I discuss some new ideas about how memes are perceived and ranked by the human brain.

I am having an interesting conversation with Howard Bloom, author, memeticist, historian, scientist, and social theorist. We have been discussing network models of the universe and the underlying "metapatterns" that seem to unfold at every level of scale. Below is my reply to his recent note, followed by his note which is extremely well written and interesting...

------------
From: Nova Spivack
To: Howard Bloom
Subject: Re: Graph Automata -- Is the Universe Similar to a Social Network?

Howard, what a great reply!

Indeed the metapattern you point out seems to happen at all levels of scale. I am looking for the underlying Rule that generates this on abstract graphs -- networks of nodes and arcs.

In thinking about this further, I think we live in a "Social Universe." What binds the universe together, and causes all structure and dynamics at every level of scale, is communication along relationships. Communication takes place via relationships. And relationships in turn develop based on the communication that takes place across them.

Relationships and communications take place between locations in the manifold of spacetime, as well as between fundamental particles, cells, people, ideas, network devices, belief systems, organizations, economies, civilizations, ecosystems, heavenly bodies, galaxies, superclusters, or entire universes. Whether you call it "gravitation" and "repulsion" and other forces are really just emergent properties of the dynamics of relationships and communications. It's really all very self-similar.

I believe that we can make an abstract model of this -- just a graph comprised of nodes connected by arcs -- where the nodes (and possibly the arcs too) have states, and information may travel across them. Then, at each moment in time, we may apply simple local rules to modify the states of nodes and arcs in this network based on their previous states and the states of their neighbors.

One of the many cool things about the Metaweb is that it functions as a vast bottom-up collaborative filtering system. RSS feeds represent perspectives of publishers. Because feed publishers can automatically or manually include content from other feeds they can "republish," annotate and filter content. Every feed is effectively a switch, routing content to and from other feeds. You are my filter. I am your filter.

Entire communities can collaboratively filter information, in a totally bottom-up way. The community as a whole acts to filter and route content in an emergent fashion, without any central coordination. On top of this sites can then provide value-added aggregation and information-refinery services by tracking memes across any number of feeds and then repackaging and redistributing them in virtual feeds for particular topics or interests. And these new feeds are fed right back into the collective mind, becoming raw materials for still other feeds that pick them up.

What we have here is the actual collective consciousness of humanity thinking collective thoughts in real-time, and we get to watch and participate! We are the "neurons" in the collective minds of our organizations, communities, marketplaces. Our postings comprise the memes, the thoughts, in these collective thought processes. Already the Metaweb is thinking thoughts that no individual can comprehend -- they are too big, too distributed, too complex. As the interactions of millions of people, groups and memes evolve we will see increasing layers of intelligence taking place in the Metaweb.

At Radar Networks we refer to pieces of microcontent as "Memes." A Weblog posting is a Meme (pronounced "meem"), so is any RSS item. The classic definition of a meme is "a replicating unit of culture." There is quite a bit of debate among memeticists about what constitutes replication and what constitutes a replicator. But in any event, here we are simply using the term to indicate that a piece of microcontent is replicable, is a unit of information (culture), and spreads across human populations. To be precise, a meme in the classical sense is really any idea, thus a piece of microcontent might contain many memes by that definition. In that view a microcontent object is actually a vector for memes it contains, as well as a meme itself in that it expresses or encapsulates the information which ties them all together. A Meme can be a compound object comprised of other Memes -- for example in classical memetics "Catholicism" is a meme comprised of numerous other memes that comprise the belief system. In the same way any piece of microcontent is a Meme that may in turn be comprised of other Memes. The fact that sites like technorati, Daypop and others are starting to index and track the link structure and propagation of microcontent objects lends credence to this terminology: they are mapping and monitoring the spread of memes. While the technology they use for this is still quite primitive, it is a step in the right direction. For now, I think the use of the term "Meme" to refer to a piece of microcontent is helpful in that it implies the fact that microcontent spreads socially across human relationships.

The Metaweb is not just the set of all Weblog posts, it is much more than that. As much as I love to blog I think many old-timers would have us view the entire Net through "blog colored glasses." But Weblog postings are just one kind of microcontent. There will be many others.

Originally developed at Netscape, a new technology called RSS has risen from the dead to ignite the next-evolution of the Net. RSS represents the first step in a major new paradigm shift -- the birth of "The Metaweb." The Metaweb is the next evolution of the Web -- a new layer of the Web in fact -- based on "microcontent." Microcontent is a new way to publish content that is more granular, modular and portable than traditional content such as files, Web pages, data records, etc.

On the existing Web, information is typically published in large chunks -- "sites" comprised of "pages." In the coming microcontent-driven Metaweb, information will be published in discrete, semantically defined "postings" that can represent an entire site, a page, a part of a page, or an individual idea, picture, file, message, fact, opinion, note, data record, or comment.

Metaweb postings can be hosted like Web pages in particular places and/or they can be shipped around the Net using RSS in a publish-subscribe manner. Webloggers for example create microcontent every time they post to their blogs. Each blog posting is a piece of microcontent. End-users can subscribe to get particular pieces of microcontent they are interested in by signing up to track "RSS channels" using "RSS Readers" that poll those channels periodically for new pieces of microcontent.

Very interesting memetics research is taking place at Microsoft. They are analyzing the distributions of statistical patterns in USENET threads to determine which threads are worth reading, and to personalize content for individuals based on their social patterns. This article has some fascinating statistics in it, as well as hints about where Microsoft is headed with all this...

A new generation of data-mining tools is emerging that uses neural nets and "Predictive Model Markup Language" (PMML). This article has more details.

I would like to start an initiative to track and measure memes (replicating ideas) as they move around the world in real-time. I've spent about a year thinking about the technology necessary to do this. It requires a lot of data-mining power, but the algorithms are fairly simple. Essentially, we mine the Web for noun-phrases and then measure the space-time dynamics of those phrases as they move through various demographic, geographic, and topical spaces.

GoMeme 3.0 - So Funny: CIA Asks Bush to Stop Blogging

Note: This experiment is now finished.

(GoMeme 3.0 - Note: This is not an ordinary article. We have added some special information at the end. Read this entire article, and then follow the instructions at the end to pass it on in a new way...)

GoMeme 2.0 - Help Test This Meme

Note: This experiment is now finished.

GoMeme 2.0 -- Copy This GoMeme From This Line to The End of this article, and paste into your blog. Then follow the instructions below to fill it out for your site.

Steal This Post!!!! This is a GoMeme-- a new way to spread an idea along social networks. This is the second generation meme in our experiment in spreading ideas. To find out what a GoMeme is, and how this experiment works, or just to see how this GoMeme is growing and discuss it with others, visit the Root Posting and FAQ for this GoMeme at www.mindingtheplanet.net .

Can You Imagine What Would Happen if MoveOn.Org Used the GoMeme Concept?

I wonder if anyone from MoveOn.Org or the Republicans will notice our GoMeme experiments? (Not that I'm taking sides -- I'll simply be happy if somebody wins the election!) Grassroots political campaigns could potentially really benefit from the techniques we're testing here. For example, imagine a "blog meme" for a political campaign -- a meme that states some useful facts about a candidate and their opponent, perhaps has some survey questions and a GUID, and has the added benefit of a cool Improve-Your-Google-Ranking-By-Hosting-This-Meme candy coating? Wow -- it could spread the message to a lot of blogs pretty quickly if done right. That might actually work. But I try to stay out of politics, so I'm not taking sides here or endorsing anyone. If you read this and know the "right people" -- feel free to suggest the idea to them.

FAQ for GoMeme 2.0

This posting is the FAQ and introduction for a new, improved, second-generation meme experiment that is designed to spread faster and more broadly than the first meme experiment. We call this kind of meme a "GoMeme" (pronounced Go-Meem), because it is a meme that is designed to Go. The actual GoMeme, which you can add to your Website is located, here. Before you do this, please read this FAQ so you know how it works.

RFC for a New Distributed Data Exchange System

Matt Poepping has come up with an interesting idea for how to create a fully distributed searchable database on the Net. It's a cool enough idea and approach that people should see his RFC and comment on it. He may be onto something important here.

A New Blogging Feature: Automated "Social Syndication" Networks

Here's an idea I've had recently that is related to the Meme Propagation experiment (see posts below on this blog for more about that ongoing experiment). The concept is for a new, meme-based, way to syndicate content across blogs. Here's how it might work:

1. You join a "meme syndication network" by joining at a central site. You get an account where you can profile your blog. You also set your blog's syndication inputs -- a set of other blogs that are also in the network that you are willing to automatically syndicate content from.

2. When you complete this, you are given an automatically generated HTML element containing a script to put in your blog sidebar, or anywhere else in your layout. This script is auto-generated for you from a central site that manages the network. The script automatically displays short excerpts for blog postings (pieces of microcontent) that have been "picked up" by your site from your registered "inputs" in the network. You place this script in your layout.

3. In the area created by the script in your site, you see a listing of blog postings that have been syndicated to your site from your inputs. You can post to your network by going to your account at the central network site and posting (or copying in the URL for anything you want to post) there. Any network-member sites that treat your node in the network as an "input" will then *automatically* pickup your posting and display it on their page.

Is Your Blog a Hot Zone?

Meme Update: The Meme is already global and the rate of growth is showing signs of exponential increase. It's made the Daypop top list, also same with Blogdex. It's made its way onto several early-adopter sites and lists. Already the results are interesting. One thing that is clear is that there is quite a lag time in Blogspace: This applies not just to blogs, but also to aggregation sites and search sites -- which don't update nearly as often as one might think.

Comments:

It seems that certain bloggers read and post much more frequently than others -- we could call their blogs "hot zones," to borrow a term from epidemiology.
.

GoMeme 1.0 -- Testing Meme Propagation In Blogspace: Add Your Blog!

NOTE: This experiment is now finished.

This is an experiment in spreading ideas across weblogs using the principles of viral marketing and social networks using a new method for making content more viral, which we call a "GoMeme."

An Interesting Visualization of Word Frequencies

This animated visualizer lets you enter a word (in the little search box on the bottom left) and then shows the word situated next to other words that are used with similar frequency in English. It's cool -- you can discover some interesting things. Read the about page for more on that. This system would be really good if it used the concepts from my paper on A Physics of Ideas. What they should do is show the words next to other words with similar present momentum. That would be much more informative and useful than simply visualizing words as if all mentions happened at once. The fact that mentions occur over time (and space) is what is really important. It is much more interesting than the mere total number of mentions since time began. I would love to see a visualization of meme momentums as I have proposed in my article above. If you feel like making one, please let me know!

A Physics of Ideas: Measuring The Physical Properties of Memes

by Nova Spivack
http://www.mindingtheplanet.net

Original: July 8, 2004
Revised: February 5, 2005


(Permission to reprint or share this article is granted, with a citation to this Web Page: http://www.mindingtheplanet.net)

This paper provides an overview of a new approach to measuring the physical properties of ideas as they move in real-time through information spaces and populations such as the Internet. It has applications to information retrieval and search, information filtering, personalization, ad targeting, knowledge discovery and text-mining, knowledge management, user-interface design, market research, trend analysis, intelligence gathering, machine learning, organizational behavior and social and cultural studies.

Introduction

In this article I propose the beginning of what might be called a physics of ideas. My approach is based on applying basic concepts from classical physics to the measurement of ideas -- or what are often called memes -- as they move through information spaces over time.

Ideas are perhaps the single most powerful hidden forces shaping our lives and our world. Human events are really just the results of the complex interactions of myriad ideas across time, space and human minds. To the extent that we can measure ideas as they form and interact, we can gain a deeper understanding of the underlying dynamics of our organizations, markets, communities, nations, and even of ourselves. But the problem is, we are still remarkably primitive when it comes to measuring ideas. We simply don't have the tools yet and so this layer of our world still remains hidden from us.

However, it is becoming increasingly urgent that we develop these tools. With the evolution of computers and the Internet ideas have recently become more influential and powerful than ever before in human history. Not only are they easier to create and consume, but they can now move around the world and interact more quickly, widely and freely. The result of this evolutionary leap is that our information is increasingly out of control and difficult to cope with, resulting in the growing problem of information overload.

There are many approaches to combating information overload, most of which are still quite primitive and place too much burden on humans.  In order to truly solve information overload, I believe that what is ultimately needed is a new physics of ideas -- a new micro-level science that will enable us to empirically detect, measure and track ideas as they develop, interact and change over time and space in real-time, in the real-world.

In the past various thinkers have proposed methods for applying concepts from epidemiology and population biology to the study of how memes spread and evolve across human societies. We might label those past attempts as "macro-memetics" because they are chiefly focused on gaining a macroscopic understanding of how ideas move and evolve. In contrast, the science of ideas that I am proposing in this paper is focused on the micro-scale dynamics of ideas within particular individuals or groups, or within discrete information spaces such as computer desktops and online services and so we might label this new physics of ideas as a form of "micro-memetics."

To begin developing the physics of ideas I believe that we should start by mapping existing methods in classical physics to the realm of ideas. If we can treat ideas as ideal particles in a Newtonian universe then it becomes possible to directly map the wealth of techniques that physicists have developed for analyzing the dynamics of particle systems to the dynamics of idea systems as they operate within and between individuals and groups.

The key to my approach is to empirically measure the meme momentum of each meme that is active in the world. Using these meme momenta we can then compute the document momentum of any document that contain those memes. The momentum of a meme is a measure of the force of that meme within a given space, time period, and set of human minds (a "context"). The momentum of a document is the force of that document within a given context.

Once we are able to measure meme momenta and document momenta we can then filter and compare individual memes or collections of memes, as well as documents or collections of documents, according to their relative importance or "timeliness" in any context.

Using these techniques we can empirically detect the early signs of soon-to-be-important topics, trends or issues; we can measure ideas or documents to determine how important they are at any given time for any given audience; we can track and graph ideas and documents as their relative importances change over time in various contexts; we can even begin to chart the impact that the dynamics of various ideas have on real-world events. These capabilities can be utilized in next-generation systems for knowledge discovery, search and information retrieval, knowledge management, intelligence gathering and analysis, social and cultural research, and many other purposes.

The rest of this paper describes how we might attempt to do this, some applications of these techniques, and a number of further questions for research.

Minding the Planet: From Semantic Web to Global Mind

Draft 1.1 for Review (integrates some fixes from readers)
Nova Spivack (www.mindingtheplanet.net)

INTRODUCTION

This article presents some thoughts about the future of intelligence on Earth. In particular, I discuss the similarities between the Internet and the brain, and how I believe the emerging Semantic Web will make this similarity even greater.

DISTRIBUTED INTELLIGENCE

The Semantic Web enables the formal communication of a higher level of language -- metalanguage. Metalanguage is language about language -- language that encodes knowledge about how to interpret and use information. Metalanguages – particularly semantic metalanguages for encoding relationships between information and systems of concepts – enable a new layer of communication and processing. The combination of computing networks with semantic metalanguages represents a major leap in the history of communication and intelligence.

The invention of written language long ago changed the economics of communication by making it possible for information to be represented and shared independently of human minds. This made it less costly to develop and spread ideas widely across populations in space and time. Similarly, the emergence of software based on semantic metalanguages will dramatically change the economics not only of information distribution, but of intelligence -- the act of processing and using information.

Semantic metalanguages provide a way to formally express, distribute and share the knowledge necessary to interpret and use information, independently of the human mind. In other words, they make it possible not just to write down and share information, but also to encode and share the background necessary for intelligently making use of that information. Prior to the invention of such a means to share this background knowledge about information, although information could be written and shared, the recipients of such information had to be intelligent and appropriately knowledgeable in advance in order to understand it. Semantic metalanguages remove this restriction by making it possible to distill the knowledge necessary to understand information into a form that can be shared just as easily as the information itself.

The recipients of information – whether humans or software – no longer have to know in advance (or attempt to deduce) how to interpret and use the information; this knowledge is explicitly coded in the metalanguage about the information. This is important for artificial intelligence because it means that expertise for specific domains does not have to be hard-coded into programs anymore -- instead programs simply need to know how to interpret the metalanguage. By adding semantic metalanguage statements to information data becomes “smarter,” and programs can therefore become “thinner.” Once programs can speak this metalanguage they can easily import and use knowledge about any particular domain, if and when needed, so long as that knowledge is expressed in the metalanguage.

In other words, whereas basic written languages simply make raw information portable, semantic metalanguages make knowledge (conceptual systems) and even intelligence (procedures for processing knowledge) about information portable. They make it possible for knowledge and intelligence to be formally expressed, stored digitally, and shared independently of any particular minds or programs. This radically changes the economics of communicating knowledge and of accessing and training intelligence. It makes it possible for intelligence to be more quickly, easily and broadly distributed across time, space and populations of not only humans but also of software programs.

The emergence of standards for sharing semantic metalanguage statements that encode the meaning of information will catalyze a new era of distributed knowledge and intelligence on the Internet. This will effectively “make the Internet smarter.” Not just monolithic expert systems and complex neural networks, but even simple desktop programs and online software agents will begin to have access to a vast decentralized reserve of knowledge and intelligence.

The externalization, standardization and sharing of knowledge and intelligence in this manner, will make it possible for communities of humans and software agents to collaborate on cognition, not just on information. As this happens and becomes increasingly linked into our daily lives and tools, the "network effect" will deliver increasing returns. While today most of the intelligence on Earth still resides within human brains, In the near future, perhaps even within our lifetimes, the vast majority of intelligence will exist outside of human brains on the Semantic Web.

THE INTERNET IS A BRAIN AND THE WEB IS ITS MIND

Anyone familiar with the architecture and dynamics of the human nervous system cannot help but notice the striking similarity between the brain and the Internet. But is this similarity more than a coincidence - is the Internet really a brain in its own right - the brain of our planet? And is its collective behavior intelligent - does it constitute a global mind? How might this collective form of intelligence compare to that of an individual human mind, or a group of human minds?

I believe that the Internet (the hardware) is already evolving into a distributed global brain, and its ongoing activity (the software, humans and data) represents the cognitive process of an increasingly intelligent global mind. This global mind is not centrally organized or controlled, rather it is a bottom-up, emergent, self-organizing phenomenon formed from flows of trillions of information-processing events comprised of billions of independent information processors.

As with other types of emergent computing systems, for example John Conway’s familiar cellular automaton “The Game of Life,” on the Internet large scale homeostatic systems and seemingly intentional or guided information processes naturally emerge and interact within it. The emergence of sophisticated information systems does not require top-down design or control, it can happen in an evolutionary bottom-up manner as well.

Like a human brain, the Internet is a vast distributed computing network comprised of billions of interacting parallel processors. These processors include individual human beings as well as software programs, and systems of them such as organizations, which can all be referred to as "agents" in this system. Just as the computational power of the human brain as a whole is vastly greater than that of any of the individual neurons or systems within it, the computational power of the Internet is vastly beyond any of the individual agents it contains. Just as the human brain is not merely the sum of its parts, the Internet is more than the sum of its parts - like other types of distributed emergent computing systems, it benefits from the network effect. The power of the system grows exponentially as agents and connections between them are added.

The human brain is enabled by an infrastructure comprised of networks of organic neurons, dendrites, synapses and protocols for processing chemical and electrical messages. The Internet is enabled by an infrastructure of synthetic computers, communications networks, interfaces, and protocols for processing digital information structures. The Internet also interfaces with organic components however – the human beings who are connected to it. In that sense the Internet is not merely an inorganic system – it could not function without help from humans, for the moment at least. The Internet may not be organized in exactly the same form as the human brain, but it is at least safe to say it is an extension of it.

The brain provides a memory system for storing, locating and recalling information. The Internet also provides shared address spaces and protocols for using them. This enables agents to participate in collaborative cognition in a completely decentralized manner. It also provides a standardized shared environment in which information may be stored, addressed and retrieved by any agent of the system. This shared information space functions as the collective memory of the global mind.

Just as no individual neuron in the human brain could be said to have the same form or degree of intelligence as the brain as-a-whole - we individual humans cannot possibly comprehend the distributed intelligence that is evolving on the Internet. But we are part of it nonetheless, whether we know it or not.  The global mind is emerging all around us, and via us, is our creation but it is already becoming independent of us - truly it represents the evolution of a new form of meta-level intelligence that has never before existed on our planet.

Although we created it, the Internet is already far beyond our control or comprehension - it surrounds us and penetrates our world - it is inside our buildings, our tools, our vehicles, and it connects us together and modulates our interactions. As this process continues and the human body and biology begins to be networked into this system we will literally become part of this network - it will become an extension of our nervous systems and eventually, via brain-computer interfaces, it will be an extension of our senses and our minds. Eventually the distinction between humans and machines, and the individual and the collective, will gradually start to dissolve, along with the distinction between human and artificial forms of intelligence.

The Memecodes Project

The Memecodes Project starts with randomly generated Web pages and evolves them to get more search results from Google. Brilliant idea. The only problem is that Google indexing isn't frequent enough, making this process take a bit of time. Still, I think this is a very interesting new approach that could even be a useful utility for sites in general someday.

New Version of My "Metaweb" Graph -- The Future of the Net

Notes:

Many people have requested this graph and so I am posting my latest version of it. The Metaweb is the coming "intelligent Web" that is evolving from the convergence of the Web, Social Software and the Semantic Web. The Metaweb is starting to emerge as we shift from a Web focused on information to a Web focused on relationships between things --- what I call "The Relationship Web" or the "Relationship Revolution."

We see early signs of this shift to a Web of relationships in the sudden growth of social networking systems. As the semantics of these relationships continue to evolve the richness of the "arcs" will begin to rival that of the "nodes" that make up the network.

This is similar to the human brain -- individual neurons are not particularly important or effective on their own, rather it is the vast networks of relationships that connect them that encode knowledge and ultimately enable intelligence. And like the human brain, in the future Metaweb, technologies will emerge to enable the equivalent of "spreading activation" to propagate across the network of nodes and arcs. This will provide a means of automatically growing links, weighting links, making recommendations, and learning across distributed graphs of nodes and links. This may resemble a sort of "Hebbian learning" across the link structure of the network -- enhancing the strength of frequently used connections and dampening less used links, and even growing new transitive links when appropriate.

As the intelligence with which such processes unfolds, in a totally decentralized and grassroots manner, we will begin to see signs of emergent "transhuman" intelligences on the network. Web services are the beginning of this -- but imagine if they were connected to autonomous intelligent agents, roaming the network and able to interact with one another, Web sites, and even people. These next-layer intelligences will begin to function as brokers, associators, editors, publishers, recommenders, advertisers, researchers, defenders, buyers, sellers, monitors, aggregators, distributors, integrators, translators, and also as knowledge-stewards responsible for constantly improving the structure and quality of subsets of the Web that they oversee. And while many of these agents will be able to interact intelligently with humans, not all of them will -- most will probably just have interfaces for interacting with other agents.

Vast systems of "hybrid intelligence" (humans + intelligent software) will form -- for example, next-generation communities that intelligently self-organize around emerging topics and trends, smart marketplaces that self-optimize to reduce the cost of transactions for their participants, 'group minds' and 'enterprise minds' that embody and manage the collective cognitiion of teams and organizations, and knowledge networks that function to enable distributed collective intelligence among networks of indivdiuals, across communities and business-relationships.

As the network becomes increasingly autonomous and self-organizing we may say that the network-as-a-whole is becoming "intelligent." But it will be several steps beyond that before it finally "wakes up" -- when the various processes of the network reach that point at which the entire system truly functions as a coordinated, self-aware intelligence. This will require the formation of many higher layers of intelligence -- leading to something that functions like the cerebral cortex in humans. It will also require something that functions as its virtual "self-awareness" -- an internal process of meta-level self-representation, self-projection, self-feedback, self-analysis and self-improvement within the network. For a map of how this may actually unfold over time we might look at the evolutionary history of nervous systems on Earth.

As structures that provide virtual higher-order cognition and self-awareness to the network emerge, connect to one another, and gain sophistication, the Global Brain will self-organize into a Global Mind -- the intelligence of the whole will begin to outpace the intelligence of any of its parts and thus it will cross the threshold from being just a "bunch of interacting parts" to "a new higher-order whole" in its own right -- a global intelligent Metaweb for our planet.

From Application-Centric to Data-Centric Computing: The Metaweb

One of the big changes that will be enabled by the coming Metaweb is the shift from application-centric computing to data-centric computing. As the Metaweb evolves, information will be imbued with increasingly sophisticated metadata. HTML provides metadata about formatting and links. XML provides metadata about structure and behavior. RDF, RDFS and OWL provide metadata about relationships and meaning.

As higher levels of metadata are adopted and added to content, the content becomes "smarter" -- more information about how to display, use and interpret the content is added to the content itself. The key here is that this metadata is added in an application-independent manner. In other words, the "intelligence" for interpreting the data is moved out of applications and into the data itself. Thus we move from "smart applications, dumb data" to "smart applications, smart data."

A data-centric world will be very different from the application-centric world of today -- for one thing, application providers will lose much of their competitive advantages (from platform lock-in and closed formats) as data becomes increasingly portable across various tools. Another big change will be in how we think about content -- rather than content being thought of as static documents, every piece of content will be more like an object with its own unique identity and behaviors on the network.

Instead of moving data around we will access these semantic data objects using Web services protocols and interact with them from anywhere like mini-online services. To edit a document we might send commands to an object that represents the document on the network, rather than actually downloading and modifying a local file.

Ultimately this will bring about a shift from desktop computing to network computing -- software will truly become a service and the business model of software will shift to be more like online service business models -- based on subscriptions, a la carte pay-per-use features, and perhaps even advertising. Data objects will be accessible from everywhere and will be responsible for maintaining their own state, relationships and contents, as well as managing their own access, rights and usage policies. These are some of the changes that will come about as the Metaweb evolves.

The Metaweb is Coming... See this Diagram...

This diagram (click to see larger version) illustrates why I believe technology evolution is moving towards what I call the Metaweb. The Metaweb is emerging from the convergence of the Web, Social Software and the Semantic Web.

Neuromarketing and Memetic Attenuation

This article discusses new research in how the brain makes buying decisions and other choices -- what is now called "neuromarketing". Neuromarketing researchers seek to discover, and influence, the neurological forces at work inside the mind of potential customers. According to the article, most decisions are made subconsciously and are not necessarily rational at all - in fact they may be primarily governed by emotions and other more subtle cognitive factors such as identity and sense of self. For example, when studied under a functional MRI, the reward centers of brains of subjects who were given "The Pepsi Challenge" lit up when they tasted Pepsi, but Coke actually lit up the parts of the brain responsible for "sense of self" -- a much deeper response. In other words, the Coke brand is somehow connected to deeper neurological structures than Pepsi.

Neuromarketing is interesting -- it's actually something I've been thinking about on my own in an entirely different context. What I am interested in is the question of "What makes people decide that a given meme is 'hot'?" Each of us is immersed in a sea of memes -- we are literally bombarded with thousands or even millions of ideas, brands, products and other news every day -- But how do we decide which ones are "important," "cool," and "hot?" What causes the human brain to pick out certain of these memes at the expense of the others? In other words, how do we differentiate signal from noise, and how do we rank memetic signals in terms of their relative "importance?" Below I discuss some new ideas about how memes are perceived and ranked by the human brain.

Social Networks, Physics, Civilizations -- Do they All Obey the Same Underlying Rules?

I am having an interesting conversation with Howard Bloom, author, memeticist, historian, scientist, and social theorist. We have been discussing network models of the universe and the underlying "metapatterns" that seem to unfold at every level of scale. Below is my reply to his recent note, followed by his note which is extremely well written and interesting...

------------
From: Nova Spivack
To: Howard Bloom
Subject: Re: Graph Automata -- Is the Universe Similar to a Social Network?

Howard, what a great reply!

Indeed the metapattern you point out seems to happen at all levels of scale. I am looking for the underlying Rule that generates this on abstract graphs -- networks of nodes and arcs.

In thinking about this further, I think we live in a "Social Universe." What binds the universe together, and causes all structure and dynamics at every level of scale, is communication along relationships. Communication takes place via relationships. And relationships in turn develop based on the communication that takes place across them.

Relationships and communications take place between locations in the manifold of spacetime, as well as between fundamental particles, cells, people, ideas, network devices, belief systems, organizations, economies, civilizations, ecosystems, heavenly bodies, galaxies, superclusters, or entire universes. Whether you call it "gravitation" and "repulsion" and other forces are really just emergent properties of the dynamics of relationships and communications. It's really all very self-similar.

I believe that we can make an abstract model of this -- just a graph comprised of nodes connected by arcs -- where the nodes (and possibly the arcs too) have states, and information may travel across them. Then, at each moment in time, we may apply simple local rules to modify the states of nodes and arcs in this network based on their previous states and the states of their neighbors.

The Metaweb: The Global Mind Just Got Smarter

One of the many cool things about the Metaweb is that it functions as a vast bottom-up collaborative filtering system. RSS feeds represent perspectives of publishers. Because feed publishers can automatically or manually include content from other feeds they can "republish," annotate and filter content. Every feed is effectively a switch, routing content to and from other feeds. You are my filter. I am your filter.

Entire communities can collaboratively filter information, in a totally bottom-up way. The community as a whole acts to filter and route content in an emergent fashion, without any central coordination. On top of this sites can then provide value-added aggregation and information-refinery services by tracking memes across any number of feeds and then repackaging and redistributing them in virtual feeds for particular topics or interests. And these new feeds are fed right back into the collective mind, becoming raw materials for still other feeds that pick them up.

What we have here is the actual collective consciousness of humanity thinking collective thoughts in real-time, and we get to watch and participate! We are the "neurons" in the collective minds of our organizations, communities, marketplaces. Our postings comprise the memes, the thoughts, in these collective thought processes. Already the Metaweb is thinking thoughts that no individual can comprehend -- they are too big, too distributed, too complex. As the interactions of millions of people, groups and memes evolve we will see increasing layers of intelligence taking place in the Metaweb.

"Memes" are the units of the Metaweb: Microcontent by Another Name

At Radar Networks we refer to pieces of microcontent as "Memes." A Weblog posting is a Meme (pronounced "meem"), so is any RSS item. The classic definition of a meme is "a replicating unit of culture." There is quite a bit of debate among memeticists about what constitutes replication and what constitutes a replicator. But in any event, here we are simply using the term to indicate that a piece of microcontent is replicable, is a unit of information (culture), and spreads across human populations. To be precise, a meme in the classical sense is really any idea, thus a piece of microcontent might contain many memes by that definition. In that view a microcontent object is actually a vector for memes it contains, as well as a meme itself in that it expresses or encapsulates the information which ties them all together. A Meme can be a compound object comprised of other Memes -- for example in classical memetics "Catholicism" is a meme comprised of numerous other memes that comprise the belief system. In the same way any piece of microcontent is a Meme that may in turn be comprised of other Memes. The fact that sites like technorati, Daypop and others are starting to index and track the link structure and propagation of microcontent objects lends credence to this terminology: they are mapping and monitoring the spread of memes. While the technology they use for this is still quite primitive, it is a step in the right direction. For now, I think the use of the term "Meme" to refer to a piece of microcontent is helpful in that it implies the fact that microcontent spreads socially across human relationships.

The Metaweb: Beyond Weblogs

The Metaweb is not just the set of all Weblog posts, it is much more than that. As much as I love to blog I think many old-timers would have us view the entire Net through "blog colored glasses." But Weblog postings are just one kind of microcontent. There will be many others.

The Birth of "The Metaweb" -- The Next Big Thing -- What We are All Really Building

Originally developed at Netscape, a new technology called RSS has risen from the dead to ignite the next-evolution of the Net. RSS represents the first step in a major new paradigm shift -- the birth of "The Metaweb." The Metaweb is the next evolution of the Web -- a new layer of the Web in fact -- based on "microcontent." Microcontent is a new way to publish content that is more granular, modular and portable than traditional content such as files, Web pages, data records, etc.

On the existing Web, information is typically published in large chunks -- "sites" comprised of "pages." In the coming microcontent-driven Metaweb, information will be published in discrete, semantically defined "postings" that can represent an entire site, a page, a part of a page, or an individual idea, picture, file, message, fact, opinion, note, data record, or comment.

Metaweb postings can be hosted like Web pages in particular places and/or they can be shipped around the Net using RSS in a publish-subscribe manner. Webloggers for example create microcontent every time they post to their blogs. Each blog posting is a piece of microcontent. End-users can subscribe to get particular pieces of microcontent they are interested in by signing up to track "RSS channels" using "RSS Readers" that poll those channels periodically for new pieces of microcontent.

Microsoft's In-House Sociologist Tracks Social Patterns in Threads

Very interesting memetics research is taking place at Microsoft. They are analyzing the distributions of statistical patterns in USENET threads to determine which threads are worth reading, and to personalize content for individuals based on their social patterns. This article has some fascinating statistics in it, as well as hints about where Microsoft is headed with all this...

Real-Time Predictive Data-Mining With Neural Networks

A new generation of data-mining tools is emerging that uses neural nets and "Predictive Model Markup Language" (PMML). This article has more details.

The Human Menome Project

I would like to start an initiative to track and measure memes (replicating ideas) as they move around the world in real-time. I've spent about a year thinking about the technology necessary to do this. It requires a lot of data-mining power, but the algorithms are fairly simple. Essentially, we mine the Web for noun-phrases and then measure the space-time dynamics of those phrases as they move through various demographic, geographic, and topical spaces.