Our Predictive Anthropology Platform uses what is referred to as a vector database, rather than a traditional relational topic database. We convert social science knowledge into mathematical data - a point in multi-dimensional space (which is explained below).
Understanding the power of our vector database requires some basic theory.
Every trend or idea in culture is impacted by two types of factors: economic and cultural. Economic factors usually involve the spending of money to popularize new ideas, while cultural factors involve the creation of new norms or ways of doing things (usually driven by the creative classes).
Let's begin with a simple example.
Let's say for argument's sake that we live in a world where consumer culture is driven by one cultural factor, and one economic factor.
Example of a Cultural Factor: Feeling a sense of control over one's own health and longevity.
Example of an Economic Factor: Only buying certain types of natural, less processed foods as a symbol of one's prosperity.
In essence, in such a world (made up of only two factors), a particular topic or trend would be represented in two dimensional space - with let's say the economic factor on the x-axis, and the cultural factor on the y-axis.
In this two-dimensional place, each topic has position coordinates. Using these coordinates, we can calculate the distances between topics using basic high school mathematics - i.e. Pythagorean theorem.
With distance, we can now begin to create a genuine model with which to track the evolution of a topic or trend over time.
First, we can examine changes in the position (coordinates) of a trend over time in this 2D space, to project where it will be in the future.
Second, by examining each topic's position relative to millions of other topics in culture, we can capture the nuanced meanings that surround specific trends and topics. And we can examine the changes in these nuances over time. After all, the study of something in culture is nothing but a study of that something in context - i.e. relative to its surroundings, and its history (as well as the history of its surroundings).
Now, here's where it gets interesting, and the power of technology and big data truly begins to shine through. Our theoretical example was in two-dimensional space, assuming that one economic and one cultural factor shaped our world.
But, the real world is impacted by thousands of such economic and cultural factors. To truly understand a trend, we must first identify the right mix (and relative strength) of all the cultural and economic factors affecting that trend. Then, we need to track the changes experienced by the makeup of these factors over time. This is key.