Memes: they’re often believed to be humorous images, videos, pieces of text, etc. that are copied (often with slight variations) and spread rapidly by Internet users. Scientifically speaking, a meme is more general, described initially in the book The Selfish Gene as “an idea, behavior, or style that spreads from person to person within a culture."
Memetic epidemiology is the study of how ideas, behaviors, and styles spread.
While this may seem like a lackluster field of research, perhaps applicable to political campaigns and sociologists, the reality is that pioneering minds are developing these methods for the purpose of process public digital data for diverse and meaningful outcomes -- and they've just begun to scratch the surface.
The information people explicitly or implicitly post about themselves on Twitter, Facebook, and other public platforms are processed in a way which provides researchers with unprecedented levels of easy-access comparative data. What it tells them sheds light on not only behaviors and opinions, but also public health, economics, and even ecology.
The potential for this line of research has not gone untapped by Sergey Brin and Nicholas Christakis. Both Brin and Christakis are involved with projects which comb through existing data to discover patterns (as opposed to creating new experiments and clinical trials which only provide the data within any given project).
It is almost difficult to convey what a significant shift in research this breakthrough creates, but this graphic from Wired Magazine does a pretty good job. What's helpful to recognize is that up until very recently, research was limited by the scope of their research team and their partners. The research teams fully plugged into the potential of memetic technology can observe and process real-time data of nearly any subject matter, on a national and sometimes international level. Even more exciting is that these veritable oceans of data don’t only provide researchers with the information that can simply help inform causation, correlation, and the difference between the two; but also allow for the observation of how ideas are spread, nuanced social behaviors, the intersection of disease epidemiology, as well as global market conditions. It really makes the "information revolution" actually revolutionary.
The challenge facing this new field is and will continue to be around the creation of data processing systems and mechanisms for handling the tremendous amount of information in ways which avoid premature conclusions or false correlations.
As Nicholas Christakis emphasizes: When we improve our methods of tracking virology or epidemiology, we don’t only build our ability to short circuit harmful contamination, we also gain insights in how we can help beneficial thoughts, behaviors, and conditions spread in ways which improve the world for all of us. Good stuff.
Do you think there is a potential application for memetic epdiemeolgy with geospatial mapping? You might want to check out Hexagon Geospatial's IGNITE Your M.App Challenge! It closes for submission in less than a week!
For more on this subject, check out the piece by Ted Radio Hour.
