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.