Influence Analysis reveals hidden intelligence in social web data

Influence Analysis reveals hidden intelligence in social web data

One astonishing fact, amongst many, about the World Wide Web is that no single entity has designed, planned or controlled its growth and development.

Despite this the Web has miraculously self-organised itself into the vast source of text, imagery, data and video that we know and love today.

The numbers and complexity associated with the Web are mind-boggling – it consists of billions of pages stitched together by literally trillions of hyper-links. In fact, the web recently overtook the human brain to become our galaxy”s “Most Complex Entity” (unless of course some distant aliens we don”t know about have got a better MCE…)

We already know that when a network becomes as complex as something like the human brain pretty amazing things start to happen. Mega-complex networks tend to give rise to stuff like perception, consciousness and personality etc.

So perhaps we shouldn”t be surprised when a network as complex as the World Wide Web begins to develop special properties too.

For instance, it”s becoming more widely recognised that some aspects of the Web, like social media activity, have an uncanny ability to reflect hidden patterns of relationship in human society and even predict (or online casinos at least pre-figure) the future.

This isn”t science fiction or some kind of digital voodoo, but a natural product of the latest complex systems science and network analysis technology.

Dollywagon has been studying this phenomena and has used its Influence Engine to map the structure and patterns of interaction within many different markets, communities and fields of interest on the Web.

Take a look at two of our latest market sector maps below. You”ll see they reveal how one community (in this case the Architectural and Construction professions in the United States) has self-organised into over-lapping sub-groups of interest and concern. The images clearly indicate who the go-to guys and influential “weather makers” are in this specific field of interest.

The data was derived from a specialised web-crawl technique that we developed which picks out the connections between web properties based on their relationship with a common theme or topic.

Our next post will look at Twitter”s uncanny ability to predict the future – enjoy!

Image 1: a Network Analysis map of the Architecture and Construction sector as found on the web (click on the image to enlarge, then click again on the next image)

Image 2: focussing in on the Architecture community (click on the image to enlarge, then click again on the next image)

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