Influence analysis maps the mind of the Market Research industry

Influence analysis maps the mind of the Market Research industry

We’ve been experimenting with making what I call ‘content networks’.

“So what?” I hear you ask.

Well, content networks might just play an ever more important role in how we analyse what people do on the Internet and social web.

When analysts study network relationships on the web or within specific social media environments, they usually hunt for real links between people or web pages. These links generally take the form of hyperlinks, comments or inter-personal connections between ‘friends’ and ‘followers’ etc.

This is a really useful thing to do, but sometimes it’s a good idea to see how people, websites or organisations are linked by ‘ideas’, ‘interests’ or ‘activities’.

This means trying to understand what specific qualities individual members of a community have in common, which can be quite a hard thing to do.

One of the easiest ways to build a true ‘content network’ is to use Twitter hash tags like #fail or #oscar etc.

Hash tags are great because computers can use them to understand what a Tweet is ‘about’. This is thanks to millions of normal people doing all the hard ‘interpretive’ work by flagging what Tweets actually mean by applying a descriptive hash tag to their Twitter messages.

If you use hash tag data creatively it’s possible to map the ‘mind’ of any market or field of interest that has a life on Twitter. My last post offers some good pictures of what this can look like.

However, the problem with using hash tags to create content networks is this – perhaps no more than a third of all tweets will contain a hash tag. This means that hash tag analysis may not be fully representative of everything people have to say about a topic on Twitter.

A more comprehensive method of creating and analysing content networks would therefore find a way to understand what web articles or social media posts were talking about and then create links between them and other similar content on the web.

This is one of the things we’re working on at Dollywagon. We’ve been mapping content relationships in the Market Research industry to see how it organises itself into defined sub-sectors and what the current hot topics are in each.

To do this we let loose our Influence Engine system onto a database of 10,000 Market Research news articles that we took from the web. The image below represents some of our early results – if you have an insider’s knowledge of this industry (which I do) it makes for interesting reading.

Click on the thumbnail to view the picture (and then click on it again to fully enlarge it), or download a PNG file by clicking here.

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