Google+ and the Search for Greater Social Intelligence
Rocky Agrawal, guest-writing for TechCrunch, does a good job discussing the signal-to-noise ratios underpinning social networks like Facebook, Twitter and especially Google+, where users manually assign people into buckets. Agrawal wrote:
The biggest unsolved problem in social networking remains unsolved with Google+: separating signal from noise. Twitter, it seems, doesn't even want to try. The timeline is as dumb as it has been since the beginning, a reverse chron firehose of information. Facebook's feed has improved over the years, but a friend in New Jersey trying to get rid of a bookshelf is just not relevant.
This is all too true! However, I disagree when Agrawal says the lack of quality tools for generating signal out of these feeds is inhibiting the creation of content. Agrawal finds himself holding back at the risk of alienating users. Brevity, it seems, is indeed the sole of wit.
I and other journalists don't subscribe to such fear. You don't like what I write in my Stream? Go frack yourself, as the good folks of Battlestar Galactica might say.
Agrawal is correct in that there is a lack of "quality tools," but have those lucky enough to participate in the Google+ field trial looked at their Stream lately? There is plenty of content; you just might not want to read most of it.
It's not that content creation is impinged, but quality content. Of course, this being a social network where human emotions conflate with logic and reason, one man's pile of schlock is another's amusing or interesting material. Subjectivity reigns supreme. Agrawal wrote:
One person I follow on Twitter actually tags most of his posts. I'm interested in his content on tech, business and aviation. But I couldn't care less about his Chicago tweets. So far, I haven't seen a tool that would learn that and automatically skip them.
Separating signal from noise and ranking disparate pieces of content is a problem that is squarely in Google's wheelhouse. The only company I've seen that has done a good job at amplifying signal is Quora.
What social software programmers need to do is employ some malleable tools and algorithms that account for the fluidity of human emotion and opinions. I used the example yesterday that:
Imagine a social network, which is static until we augment it, whose graph changed based on cues or signals its users leave. So the software notes that Mandy and Mindy are engaging in a flame war online, then changes their "friend" status to something else.
Of course, that assumes Mandy and Mindy have bared their beefs online. It won't translate from offline to online without some sort of input.
So what we clearly need to do is find a mechanism where peoples' input is absorbed and digested by the software, which accounts for life's normal changes. Quora's approach is Q&A style. That won't wash for a broader social network. Not everybody is seeking answers to questions all of the time. Sometimes they just want to hang out.
As BFFs, Mandy and Mindy may not be angry at each other forever, and we need to allow for such changes. It's just not clear how to do it.