It's a familiar litany now, that the openness and transparency
of social media will unleash a wide range of compelling outcomes for our
organizations, if we'll only embrace it. While there is little doubt
that social media is one of the great phenomenons of our age, there are
certainly those that think the hype surrounding it is also a bit
over-egged.
Yet a growing set of compelling examples
is showing us unique and vitally useful outcomes that are only possible
in social media. For those just catching up with the story, part of
the uniqueness and power of social media is that it generaly makes the
information that's shared -- using social networks, blogs, and other
forms -- public by default.
This is in contrast to earlier forms of analog and digital
communication, where we were required to have perfect foreknowledge of
who should be involved in a conversation, such as their phone number(s),
e-mail address(es), or other contact info. Everyone else was
automatically excluded from the process and the contents of the
discourse itself was largely invisible and left little behind.
In sharp contrast to this model, as we've learned through a decade of
global online experimentation, is that it's often best when we don't overly call-out the precise identities of those we wish to converse with. Instead, we've discovered that it's better for us to let those who find value in what we're saying to find us
by what we say (typically via search or recommendation by friend or
technology.) This enables us both embrace and enable serendipity,
emergence, and open innovation and this -- as MIT's Andrew McAfee
recently pointed out for the business world --- lets us bring enough of the right people together dynamically to create the most interesting and useful results possible.
The result is a rich tapestry of conversations and information that
everyone can join in on if they desire, or benefit from later on.
It's also turned out that the default public mode of social media, though it can also cause no end of headaches for companies in industries where information tends to be very private and controlled,
allows us to realize certain very significant new scenarios that older
communications technologies simply couldn't (or sometimes, just
wouldn't.) What scenarios you ask? The most important and broadest one
is letting us perceive virtually all global conversation across social
media in real-time and then analyze it. While observing such
conversations has been possible for a while, the timeliness hasn't been
easy to achieve. The same for effective and meaningful analysis.
Scale is the first part of the problem with such timely analysis of
social media, especially when it must be thorough and accurate. As I
pointed out in my last post,
that there are hundreds of large social networks, millions of blogs,
and countless online communities and forums to look at and engage with.
Important and business relevant conversations can be found in far-flung
corners that must be examined, or we potentially pay the consequences.
As Douglas Merrill observed last week in the Harvard Business Review blogs, adding new signals is one of the single most valuable ways to improve data analysis.
Thus, forging an integrated picture that truly conveys the constant
and endless stream activities and insights within social media
conversation is a relatively new phenomenon, enabled by a growing raft of so-called "big data" technologies like Hadoop and Mahout.
Isolating relevant meaning from the noise
is the second part of the problem, because the form and content of
social media is relatively unstructured and informal. It's also filled
with rich media, particularly pictures, as well as video and audio.
Given the vast diversity inherent in the nearly 1.5 billion worldwide
participants, including their language, cultures, customs, and idioms
and it's clear that even if we can actualy process all of this
conversation quickly enough, making sense of it all is as big -- and
probably much more substantial -- a challenge.
Yet perhaps it really doesn't have to be all that hard, depending on
what we're trying to accomplish. In collecting compelling examples of
what we can do by simply by listening to and analyzing social media, it
quickly becomes pretty obvious that we don't necessarily have to boil
the entire ocean of scale and semantics when it comes to making social
media strategically useful. In fact, some of the best examples often
take relatively simple data sets and infer the meaning by combining them
together with straightforward geographic visualizations, for instance.
That said, the more signal and analysis we apply, the more accurate and
useful the insights will be.
While it's clear that we're still in the early, formative stages of
social media analysis, it's equally clear that there is a great deal of
business and civic utility in applying its techniques to our lives and
work today. I've collected 10 good instances of what's possible, with
thanks to Tom Raftery of Greenmonk for identifying some of the stellar examples in this gallery.
Note: The stream graph in the visual above was generating using Twitter StreamGraphs.
A stream graph is a common technique employed to visualize the shape of
the conversations over time. This graph shows the most recent 1,000
tweets involving ZDNet on the afternoon of November 7th. It shows that
conversations about 'Microsoft', 'Skype', and 'mobile' were the most
interesting -- or at least the largest -- public conversations of that
time period about ZDNet.
8:37:00 AM
valgeo
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