We are building a social media analytics tool to turn social media monitoring into social media action. We go beyond mentions to let you Explore, Discover and Engage with the tribes talking about your brand.
Every webpage is a latent community. Each page collects the attention of people interested in its contents, and those people might well be interested in conversing with one another too. In almost all cases the community will remain latent, either because the potential ties are too weak, or because the people looking at the page are separated by too wide a gulf of time, and so on. - Page 102.
Today we were at the IBM Smart Work Summit in Melbourne
As we continue the conversation about HiveMind and the concept of mining the signals in an organisation to work out what people's expertise really is, one common question is "but can it work"? Peter Sheahan had the key note speech and in it raised a great example from Google which demonstrates clearly how the concept of mining hidden signals can deliver real world value.This comes from Google's Flu Trends site, what it shows is that by mining the common search terms related to cold and flus, they can (very) accurately track flu occurences based on searches for flu symptoms. Not only this, it's a leading indicator over the data from Doctors which takes time to aggregate. Similarly, we believe that by mining a broader range of signals within an organisation, for example what people blog about, e-mail about, contribute and comment on, check-in and perhaps yes, even search for in your Enterprise Search solution, we can mine a clear profile of their expertise.
I've been fascinated by these Hidden Signals in organisations for a while now. In some ways the original inspiration for HiveMind was this Tweet back in January 2009 where I tweeted the following:A good layoff indicator is LinkedIn, my network activity is way up - 1st action when laid off is to connect and seek recommendations. http://twitter.com/timbull/status/1159905073
Total minutes spent on the site doubled in January to 96.8 million, from 47.6 million in December.Part of what is driving all the activity is people looking for job, and helping friends who are out of work. Recommendations are up 65 percent since December, says spokesperson Kay Luo.
Most of us are already well aware that we leave a footprint on any social networking site, and in some instances, may come to regret that photo we posted on facebook. What I find more fascinating however is how these sites are generating new signals and measures that over time could be used to perhaps supplement or replace existing messages. One person updating there resume is not newsworthy - everyone updating it sends a strong message about job security. Good systems are those which can make visible these hidden messages and signals. What hidden signals are you observing in other systems which provide insight (of any kind)?
One of the things I love about Twitter is the short-thoughts you stumble across. A well crafted tweet is worth a thousand words perhaps?
Mike Gotta is the Enterprise 2.0 and Collaboration analyst at Burton and I've had occasional dealings with him in the past. He's always been insightful and provided some good background analysis to what's happening in the industry. His tweet today caught my eye:"process-centric collaboration is quite powerful - but not a new concept - "contextual collaboration" circa 1999 kicked that off"
The one question you need to ask yourself is this: what is my purpose for connecting? Connecting just to connect is aimless.
How do you tie better collaboration to the bottom line? We can save time finding answers, etc. and you can do some correlation, and that’s your cost savings or productivity increase.
We've launched our first product video over on the website and thought we would also share it here. This is meant to be a brief, highlevel introduction to HiveMind and the problem that it's trying to solve. Comments and feedback are welcome.
