“How cool is it to see a meme?”: that’s the question Philip Sheldrake asked in this must-read post (Can you see it? Making influence visible) to summarize a key concept for the future of Social Web Analytics: gathering the data is no longer the issue. “The next biggest challenge”, to paraphrase him, is about making the data –exponentially growing amounts of data- easily understandable and actionable to marcom professionals. That’s where information visualization kicks in.
“How cool is it to see a meme” then? Well, probably very cool, provided you can actually pin it down and make it show it up on a screen. But memes are, to say the least, elusive and hardly predictable (but that could change…) in the way they spread like wildfire above and below the surface of the “visible” web. It’s a bit like stormchasing, although a lot safer.
We have actually been working on this very issue, to provide our clients with the ability to not only monitor the viral spread of a blog post, or viral video, but to actually see it propagate from one site to the next, from within one community to the web at large. When you’r e in the agency business, it’s one cool thing to be able to get the buzz going about a product, it’s an even cooler one to be able to show your client (and your client’s client) where, when and how it went viral.
Having built the most comprehensive map of the US political web for the 2008 Personal Democracy Forum, we had an ideal dataset to overlay the spread of two of the most blogged-about videos of this electoral cycle: John McCain’s “Celebrity” attack ad, and Paris Hilton’s blockbuster response.
Naturally, the Hilton video propagated well beyond the limits of the “political web” (a dataset of the 4,000+ leading sites and blogs covering US politics). With over 2700 direct links to the video (according to Google Blogsearch) and more than 3 000 000 views at the end of August, the Hilton response video dwarfs the stats of the initial McCain (as shown in the graph below).
Aside from these raw numbers, the animated visualization below provides us with a glimpse of the dynamics of propagation over time on the political web: who’s blogged about it first, who picked up on it among progressive or conservative communities (with direct links to the post and authority ranks for each one of them). It is clear, from this viral propagation map, that Paris Hilton’s video -unsurprisingly- elicited more “buzz”, within the U.S. political web, than the original McCain ad.
But this is not just about creating cool animations. This type of data visualization has, time and again, provided us (and our clients) with the ability to answer three (out of six) open questions asked by Philip Sheldrake in his post:
- “Who’s most likely to have started this rumour?” [all content is indexed and time-stamped, making it easy to spot the “fire-starter” blog at the onset of the animation* and track propagation henceforth]
- “Who or what is exerting most influence?” [everyone’s got their own ‘secret sauce’ to determine influence on the web. Ours is called the "lnkfluence score" which is essentially based on one's site relative position of authority within its community (see this primer for more details)]
- “Who should we add to our list of key contacts / influencers?” [here again, visualization comes in handy: key influencers don’t exist in a vacuum, they are positioned at the center of their own community of readers and peers. They are first and foremost, hubs of information absorption and dissemination, showing up as large ‘nodes’ (larger dots) in the social graph.]
As to Sheldrake’s conclusion about the beauty of some visualization, well, we do our best, but no one could fault you if your preference went to watching the meme itself, especially one that’s wearing a skimpy swimsuit and shiny high heels 
*In the case of the Celebrity and Paris Hilton videos, there is no single “fire-starter” website, as both videos received considerable paid and earned media exposure, both off-line and online. Although it should be noted that the Progressive community, acting as an aggregate trigger of online discussions, moved faster and displayed more interest in the end than the Conservative community online.
