There has been a lot of press around the Iranian elections and how social media is facilitating rapid sharing of information. The amount of news on this subject is dying down so now is a perfect time to reflect on what we can learn from this event. Twitter has received a bulk of the notoriety and is showing it's value as a real-time news feed from the street. The relative ease of sharing pictures and video makes it even more compelling (check out picfog.com as an example.)
There is some interesting analysis we can do with the data generated by this event. It's becoming easier than ever with all the trending and search tools available for Twitter. If we start by looking at trend data for the #iranelection hash tag we get this (using Twist):

(For those of you that don't use Twitter a hashtag (#) is something manually typed in to stay on a topic with others)
Since entering the hashtag is a manual process is there something automated that would have highlighted the rise of this hashtag? Let's try looking at some other terms that are relevant, but not as contrived as #iranelection:

This data is trending up similarly, so let's drill into the early days just after the election:
From this view it's clear that the words Iran, Election and Ahmadinejad started to get more active about 24 hours before the #iranelection tag was being used and 32 hours before it really took off.
Does this provide any value from a security visibility perspective? I think it does. Discovering anomalies and trends is an important part of an effective security program. Analyzing distributed events like this provides insight into human crowd behavior. For example, what if the #iranelection tag was automatically generated 24 hours earlier? What if people that were tweeting with the words Iran, Election and Ahmadinejad were told about the tag and started to use it earlier? How many of these tweets are SPAM riding the wave of activity...well, that's a good topic for another post :-)
This also highlights techniques that we can use in our infosecurity world to discover threat trends. Are you capturing data from all your security and networking devices and analyzing these events? Do you analyze network traffic ("the crowd") for emerging trends? Could you implement a process to get better visibility into security events as they occur?
The tools and techniques are out there that make this very feasible in complex and distributed networks. Are you leveraging them?