Getting social, in the background, randomly, or inferentially

Most of the time, writing about social business revolves around foreground activities, like how people might use new tools, or actions that leaders can take to coax a company’s culture along, step by step. But a few things from last week cause me to reflect on the possibilities for social tools and practices that take place in the background.

Spreadd is a new tool in beta (see Spreadd is a smart eavesdropper, building profiles in the background and making connections), that typifies what I mean by running in the background. But I will generalize their model a bit, to get at what I think is the most promising trend: finding the right folks to follow. Imagine your company uses some well-known tools that have APIs that tools like Spreadd can integrate with, so that as you and others upload files into Dropbox, post contacts and deals into Highrise, emails exchanged within the firm, or the stream of discussions in Yammer, that information can be mined and analyzed, and a taxonomy of topics derived.

After some point, such a background tool could reach the point of having a better picture of what people are concerned with, and interested in. And then, introductions could take place. For example, Karl Huo, a manager at AdjectiveNoun might receive an email suggesting that he have coffee with Bette Grimes, who appears to be interested in new product innovation approaches, and whom he has not met, since she just joined the company. Or Bette might be introduced to the author of a document in a public folder on the company’s Dropbox that details a survey of the company’s past product development techniques, which might be helpful in her role as product manager.

The most important decision in a connected world is who to follow, and therefore tools and techniques that increase the likelihood of making useful ‘follows’ are potentially the most valuable.

I recently commented on the growing adoption of randomly introducing people in large companies, and suggesting they  have coffee or share a lunch (see Playing roulette at work). Randomness may add some playfulness to getting social, and reduce any expectations about the possibility of some innovative idea or long-term working partnership coming from the coffee break. I haven’t heard of it being done, but randomized groups having lunch together might be interesting as well, and perhaps might lead to more tangible results in a shorter time. And, at the very least, the company benefits from more connections: since these chance interactions have some possibility of leading to friendship, the activity is worth trying. It’s been shown over and over that employee engagement is increased by increasing connections and friendships at the office.

I am a strong advocate for tags, at the very least as a means to indicate the realms of discourse that a post, document, meeting, task, mention, or update might be connected with. But, it may be even more important as a mechanism to find common purpose from otherwise unrelated individuals, especially across different tools. Imagine that Bette had been using a company wiki to collate various documents related to her project, and that Karl Huo principally confines his contributions to Yammer, which is not integrated at the company. But background bots might discover similar or related terms in use by the two, or simple searches by either might do so as well.

But when people are connected, we might use tags as a way to winnow out those things from them that we want to see, and filter others that are less interesting. I imagined this sort of people tagging last week in Cooperative tools need to become ‘engines of meaning’:

[…] imagine that I am following a colleague, Bette, on an imaginary cooperative tool, Koan. Koan (let’s imagine) implements a user tag-based filtering. So I could tag Bette with ‘Jones project’, ‘social business’, and ‘NYC’ and then messages that match those tags would surface in my stream.

This requires the Koan system to be very knowledgeable about tags, and to be able to cluster them, like Flickr does, in order to infer things that I would like to see. So when Bette tags something as ‘Manhattan’ or ‘Times Sq’, Koan should pass it along to me. And, following in the footsteps of Azendoo, anything public, or private that I am privy to, regarding the Jones project, I should see. And if she has some breaking news about Yammer or Tomfoolery to share, the social business tag should suffice to pull that information into my stream.

Note that these ‘search tags’ must be interpreted liberally, and not limited to looking just at the explicit tags offered up by Bette. In particular, tags and terms of other users, commenting on Bette’s messages, would be important, even if I am not following them.

Years ago, in 2006 and 2007, I advanced the idea of ‘groupings’ as a replacement or extension of groups. I made the case that all the people using a tag or searching for it represent a ‘grouping’ which has similarities to a group or a context, but which is very different. No one has to invite me to use the tag ‘social business’ or to search for it. I opt to do so without the tag being ‘owned’, and participation in the grouping is very unlike membership in a group. There may be reasons to allow people to define tags that are ‘private’, meaning they define contexts, but I bet in the future the proportion of closed tags will decrease as part of the explosion of connection as we move to a cooperative world of work.

In effect, I am creating an explicit collection of people who I tagged as ‘social business’ connections, but it is a loose grouping since I tag them individually: they aren’t being invited to a defined group. And a tool like the fictional Koan would interpret the tags loosely, deciding that a mention of Jive or Spreadd by Bette should show up in my inbound stream even if it weren’t explicitly tagged ‘social business’.

There needs to be a lot more innovation in this area. One of the topics that I heard discussed a great deal at last week’s Social Now conference was ‘stream fatigue’ or ‘social fatigue': there is too much information streaming in to the users of social tools because we don’t have adequate filters, and techniques that connect us to more people will only make this worse. As the world slides into fast-and-loose, we need better ‘engines of meaning’ (as Bruce Sterling styled it) or we will suffocate in the social exhaust of industrial-scale networks.

Relevant Analyst
Stowe Boyd

Stowe Boyd

Lead analyst Gigaom Research

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