Social Media Measurement: Part 1
This is Part 1 of a new series that explores the science of Social Media Measurement.
Much attention has been given to the Web 2.0 generation of social networks and websites. Deservedly so, this next wave of Internet properties has quickly acquired humongous user bases, rich valuations, and cultural buzz worldwide. Venture capital investors are clamoring to fund the latest spin on crowdsourcing, content aggregation, social networking, micro-blogging, video sharing, and other different takes on social media. Fortune 2000 companies are all trying to figure out how to respond to this phenomenon; after all, they do need to be where customers congregate.
One of the big problems in this space is that advertisers and marketers are being duped by self-branded “social media gurus” and “social app gurus” who market their simplistic consulting and shoddy development services while demanding rich retainer fees. They promise “viral” adoption of inane and mundane “social networking apps” that lend little credibility to the corporate buyer. They promise “branding” efficiencies and opportunities by continually repeating their mantra of getting their clients “into the conversation.” But all good skeptical buyers should ask, “What does that conversation bring me?” More importantly, “How do I measure the effectiveness or ROI of anything that I am contemplating buying?”
At the root of the problem is the inability of the self-styled “gurus” to measure their effectiveness. Granted, social media and social networking are new fields and reliable metrics have not yet been developed. Nevertheless, progress is being made and this series will explore the emerging field of Social Media Measurement in order to bring some light and hope to what seems like a dark swamp of self-promoters looking to feed at the corporate trough.
Popularity, Novelty, and Attention
These three components are difficult to measure, but are critical to understanding how well a certain social media campaign is running. Any “guru” that advertises their expertise ought to be able to explain popularity and attention. Novelty is a little easier to define, we know what is new when we see it.
One of the great movements of Web 2.0 is the method of crowdsourcing. Crowdsourcing can be defined as “leveraging a community (this needs to be more thoughtfully defined) to gather intelligence or opinion.” It is what James Surowiecki explores in his book, The Wisdom of Crowds, and what Tapscott and Williams explore in their book, Wikinomics: How Mass Collaboration Changes Everything.
One of the great companies that has figured out a way to harness the power of crowdsourcing is Digg.com, a website that allows users to essentially vote or “digg” for interesting stories, articles, and blog posts. The items that receive the most votes rise to the top and garner even more attention. It is a useful website for finding out about what is important to others. Essentially, Digg is a good source of finding out about a particular story’s popularity, novelty, and attention.
Fang Wu and Bernardo Huberman, two researchers at Hewlett-Packard’s (HPQ) Palo Alto, California laboratory recently released a study exploring the mechanics of Digg. They essentially developed a mathematical model that describes how the popularity of a story decays over time. This decay algorithm is not unlike that which describes the half-life of radioactive material. Another victory for the Latticework Model of multidisciplinary scientific inquiry. At the core of their model is a function called a stretched exponential relaxation, which achieved the ability to measure the half-life of prominent Digg stories. Digg’s extremely popular front page, which has the power to generate vast amounts of Web traffic to stories that make the front page, features a half-life of 69 minutes! It takes a lot of work to get onto the front page of Digg but all that cumulative work results in a premium of just over 1 hour of premium attention.
I do have problems with this study and its conclusions. My issues aren’t with the conceptual idea of measuring popularity, novelty, and attention. I have caveats about their study design and assumptions. One of the well known secrets of Digg is that there are relatively select groups of Digg members who hold disproportionate influence in the community. Almost all the stories they “digg” or submit to the community habitually show up on the front page or home page. Everyone knows that there are ways to game the Digg engines. One could imagine loose “tribes” of Diggers that “help” each other digg stories in a reciprocal manner in order to get their stories to the top. This reciprocity has little to do with the novelty or newsworthiness of a story.
Another problem with the study design and assumptions is that a community is only as good or valid as its component parts. In other words, the demographic makeup of a community obviously is an overwhelming factor. Digg is a notoriously young and tech-savvy community. As such, it has its own built-in biases. Any study should take this into consideration. Most of the stories that make it to the front page are going to be technology-focused. And even within technology, the focus is primarily on Web 2.0 stories. One would find the community very hostile to Microsoft (MSFT) and other older, first generation technology companies. I think this is a secondary concern, but it should definitely be taken into consideration.
I would have liked to see Wu and Huberman explore the concept of influence. Those super-diggers who have an extraordinary ability to push their stories to the very top. In my next post, I will explore a very rudimentary measure of influence based on another very popular social media Web service.
What are the implications of this story? Perhaps a corporation contemplating a viral campaign on Digg to try and push awareness of their story could measure the costs of such an effort. Would the ability to identify the super-diggers who might be willing to trade influence for monetary compensation be a worthwhile endeavor? Note that the community would frown upon a paid campaign to push awareness. Are the risks of negative attention worth the benefits of getting a chosen story to the top? Can 69 measly minutes of premium attention be worth the costs?
Again, I issue a warning to corporate buyers. Be very skeptical of self-branded “social media gurus” and “social app gurus” – they likely are not able to quantify their expertise and will be unfortunate resource wasters. Believe me, the talent in this cottage industry is very weak but great at self-promotion. The emergence of the new Social Science will alleviate this problem by helping advertisers, marketers, and strategists identify and measure ROI and performance. New metrics are arising everyday.