We’ve seen CNN get slammed (via the #CNNFail hashtag on Twitter) for not doing a timely job of covering the nascent election results and ensuing reaction on the ground.

We’ve seen CNN ironically run a pre-scheduled show (Reliable Sources) on the very topic of Twitter and other social media and their questionable relevance in a world of network news and (known) talking heads.

But we’ve also seen the realization that with many conversations and an exploding number of sources from which to choose from, we begin drowning in the overhead of deciding what to follow and where to focus our attention. In a rapid news cycle with new sources and new faces, we don’t know what’s good. We don’t know who is reliable. We don’t know where the trusted voices are.

3. Buyer Beware

Nothing on Twitter has been verified. While users can learn from experience to trust a certain Twitter account, it is still a matter of trust. And just as Twitter has helped get out first-hand reports from Tehran, it has also spread inaccurate information, perhaps even disinformation. An article published by the Web site True/Slant highlighted some of the biggest errors on Twitter that were quickly repeated and amplified by bloggers: that three million protested in Tehran last weekend (more like a few hundred thousand); that the opposition candidate Mir Hussein Moussavi was under house arrest (he was being watched); that the president of the election monitoring committee declared the election invalid last Saturday (not so). -source

And this is because we have very little in place that can provide us with credentials for these new voices. They’re all equal and they’re all anonymous, until we work through the quality of their content on our own (which is very time-consuming and expensive from the perspective of the news-hungry individual).

5. Twitter Is Self-Correcting but a Misleading Gauge

For all the democratic traits of Twitter, not all users are equal. A popular, trusted user matters more and, as shown above, can expose others who are suspected of being fakers. In that way, Twitter is a community, with leaders and cliques. Of course, Twitter is a certain kind of community — technology-loving, generally affluent and Western-tilting. In that way, Twitter is a very poor tool for judging popular sentiment in Iran and trying to assess who won the presidential election. Mr. Ahmadinejad, who presumably has some supporters somewhere in Iran, is losing in a North Korean-style landslide on Twitter. -source

We need a system in place whereby the community itself (read here: The Internet) can continuously and collectively vet these voices and provide a contextual backdrop on what a particular actor knows about. We need the ability to see and hear the collective’s live opinion on the sources themselves – as well as a continued eye on the content they’re producing.

Now that everyone really can have a global, instant, “retweetable” voice – we need to know who’s doing the tweeting if we want to believe the content before digging through our own vetting process. We grant authority to The New York Times and The Washington Post – largely without questioning their sourcing. If they say something, we run with it. We should get to the point when we can do the same with individuals we don’t personally have a relationship with (mediated or otherwise).

This need is being demonstrated with ad-hoc tools like twitspam.com and posts like this one specifically about the Iran Election and trusted sources.

Perhaps this is another case of the academic seeing everything from the perspective of his own problem/solution, but I sincerely feel a huge opportunity for whomever can get a robust expertise market online and available for exactly these kinds of moments. Contextual Authority Tagging…

Eugene Eric Kim has written a wonderful post on the Blue Oxen Associates blog about his use of my ideas around Contextual Authority Tagging in his work with organizations regarding reproductive health.

Terrell’s premise is that reputation in context can be extremely valuable, often more valuable than what you say about yourself. For example, suppose you asked me for three words to describe myself. In a work context, I might say, “collaboration, transformation, do-gooder.” That is how I perceive myself, or at least how I want others to perceive me. Those three words have gone through a personal filter, which may be filtering useful information. Maybe I’m too modest to say certain words. Maybe I’m deluded. Or maybe I simply don’t know what others value most about me.

There are three interesting pieces of information here:

* What do others say about you?
* What’s the difference between what others say about you and what you say about yourself?
* If you and everyone else get to see what is said about you, how will what is said evolve over time?

I’m anxious to see what Terrell discovers about these and other questions. If his premise is correct, then there are all sorts of interesting applications of this. For example, many knowledge management tools include some sort of expert finder, which is generally reliant on what people say about themselves in their personal profiles. It may be more valuable to have an expert finder that’s oriented around what others say about you.

He’s included some Wordles of the types of information and interactions that come from having people share stories and talk about one another.

Earlier this year, I facilitated a strategic workshop for Civil Liberties & Public Policy (CLPP), another reproductive health advocacy and leadership organization, and I kicked things off with this exercise. The visualizations from that exercise are particularly instructive. Here is a visualization of all the words that the participants used to describe each other:

This is most rewarding to me – and I look forward to working with Eugene in the next few months on some collaborations. I think we have a lot to offer each other in the ways we see these tools.