When you think about metrics for social media analytics, I'm guessing the ISO's seven-layer Open Systems Interconnection model isn't the first thing that comes to mind. Or the last. Or anywhere in between for that matter.
"The basic thing that's missing is a universal framework we can all agree on and work off of," Sponder said during an AllAnalytics.com instant e-chat on Friday. "Think of the network theory that most communications is based on seven layers of information all the way from the device level and back (i.e.: TCP/IP, application layer, etc.). We need that kind of framework so we can create metrics and sub-categorizations around it."
Such a framework would enable automated ways to do source identification, crawl and extract data sources, and report on key performance indicators in a standardized analytics platform, for example. Such a social media analytics framework was but one topic Sponder expounded on during last week's chat. It's a hugely critical issue, however, as he also broached in his book.
"I know firsthand that standards are necessary for the social media analytics field to mature to the point where it can interoperate with other business research disciplines," said Sponder, citing his experience building the social media committee while board director at the Web Analytics Association from 2007 to 2009.
But John Barnes, an AllAnalytics.com blogger and social media analytics watcher, suggested that finding a place with a long-term commitment to development of a "good, universal framework" could be tough. "It's too new for the universities right now, and the innovative private labs like Bell, Westinghouse, IBM, etc., are sadly fading from the picture as the immediate bottom line considerations take over," he wrote during the chat.
Sponder has a few suggested starting points. For example, he pointed to efforts under way within the Internet Advertising Bureau Social Media Council. He called out a paper put together by Richard Pentin, a member of the IAB Social Media Council, that "proposes defining and measuring core key performance indicators by social media platform, marrying software metrics with hard financials." In "A New Framework for Measuring Social Media Activity," Pentin defines the "Four A's" of social media measurement: awareness, appreciation, action, and advocacy, Sponder said.
Facilitating standards creation requires empowering organizations such as the IAB and other standards bodies "to do that for us by participating in them." One of the most exciting, "sexy" efforts to participate in, Sponder noted, is the Web Science Trust, "headed by none other than Tim Berners-Lee and his cohorts and operat[ing] as a 'trust' to study Web science."
As critical as standards work is, Sponder acknowledged that resistance is par for the course, as well. "I understand many platforms resist standards because they inhibit innovation and are somewhat forcing transparency, which may reveal more than what the platforms would like others to see and know about them."
But, if a standard and automated framework were available for mining data from social sites for business intelligence purposes... well, that'd be pretty cool, participants in the chat agreed. As Barnes said, "You'd pretty much have the problem knocked."
magneticnorth, perhaps a better way to think about what's needed is less in terms of rigid standards and more in lines of guidance or a framework. The importance, as Sponder points out in his book, is to make sure the social media analytics field matures to the point where it can interoperate with other business research disciplines.
I agree with "small steps," but I'm not so sure how analytics providers could go about this. To begin with, the social media world is so dynamic that any standard you set today can easily be overturned by a new feature introduced the following week. Also, a lot of the important metrics aren't very easy to measure on social media, as in your example on calculating a person's influence. I think only RAD on steroids can work in this case.
Lately, I've been involved in multiple discussions over the small steps Klout (a consumer-centric tool) is making in measuring social media data right now. Already they claim to be the standard but the metrics used to calculate a person's influence is greatly flawed. I look forward to a more accurate future for these kinds of tools. A standardized methodology and framework would be excellent.
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