Reposed from the Hearsay Social blog – See the original post here

One of the things I love about working at Hearsay Social is the freedom to explore new tools and methods of analysis. I recently spent some time digging into the open source data visualization program Gephi and decided to share some of the insights I came across.

Many marketers still measure the value of their social media pages by a count: either a count of fans or a count of engagements (likes, comments, etc.). Unfortunately, the insights provided by these measurements are nominal. If you want to know the true value of your fans or how your social media communities are contributing to real ROI and sales results, then these basic counts should be a start, not an end.

We have already learned that not all fans should be valued equally and that local fans can be worth as much as 40x that of corporate fans. There are additional ways to analyze a page – one of which is by viewing the composition of its fan graph as a network.

Below is an image representing Hearsay Social’s Facebook business page. The data used to create this visualization is all of the public posts, likes, and comments over a one-year period. Each point on the graph represents a fan and the edges (curved lines) between them represent shared interests as determined by common stories they interacted with.

It’s not just a pretty graph. After analyzing the image, here are a few important takeaways our data team has come up with:

1. Your entire fan base is actually made up of many smaller groupings.
   At the time of this writing, our Facebook page has nearly 5,000 fans. You can see from the image above that those fans make up a number of smaller clusters – about 20 by my count. Each of these sub-groupings has a distinct personality, set of interests, and motivation for interacting with your page. Understanding more about your own Facebook page’s sub-groups will let you better segment and target your messaging to increase its effectiveness. This is a very common practice in email marketing but it has not yet seen widespread application in social media outside of some very basic geographical targeting.When thinking about your business, you can probably think of a few sub-groups of customers. Are each of those present on social media? Are some more prevalent than others?
2. You have power fans and influencers — each with their own personality.
   Below is the same graph above, filtered by the most active fans of Hearsay Social. You can see that while there are a dozen or so power fans, they do not all share exactly the same interest. Much like the sub-groupings, each power fan has their own reason for interacting with your content. Many of these power fans are in fact strong representatives of a sub-group. Identifying these people can help you better understand how to effectively communicate with the sub-groups they share the most in common with.
   Have you identified your power fans? Do you know which sub-groups they represent?
3. Clusters of fans that have interacted with the same content can help us infer social graph connections and use Facebook’s EdgeRank to our advantage.
   Below is a magnified image of a single sub-group. Digging deeper, I traced down the common interest that these fans share: a blog post about Starbucks CEO Howard Schultz visiting the Hearsay Social office.  Most of them aren’t common ‘likers’ of content which makes us suspect that their having seen the content – and thus liking – was in part caused by Facebook’s EdgeRank. (Facebook doesn’t show every post a page makes to all of its fans but tends to show it more to people who’s friends have interacted with that content.)
   
   
   I’m not certain that anyone in this sub-group are Facebook friends with each other, but I suspect a few might be. In this case, we only have a few data points for this particular sub-group; the more data we have, the more accurate our predictions will be. (By the way, if anyone listed below happens to be reading this, leave a comment below to let us know if my hypothesis is correct!)

In conclusion, thinking about your social media connections as merely a number greatly limits your ability to understand them. The more complex your analysis model, the better your understanding will be. Social media is all about connections and networks, so one of the best ways to analyze and learn about your fans is by viewing them as an interconnected network graph.

Do you notice anything else interesting in the images? I’d love to hear your observations.