Twitter During Emergencies

Photo courtesy of DahKohlmeyer

A few months ago on the University of California, Irvine campus we had an incident in which a student wearing camouflage was seen walking onto campus from secondary road coming from a somewhat remote area (grain of salt: we are in Irvine of course). Given the stories about violence on campus that are consistently told in the main stream media, this caused people who saw him to become alarmed. The fear was that his intention was to massacre a number of students in a Virgina Tech style rampage. What followed was an explosion of real-time information sharing. It was an extremely heterogeneous mix of media that was involved however. One system that was involved is called ZotAlert. It is a terrific text-message based system that is used by the UCI Police to send text messages about emerging danger to the entire University community. It has been used to warn about violent incidents occurring in and around campus as well as burglaries and other crimes in a very short window of time after they are reported. Of course, individual text messaging, facebook, twitter, email and a variety of less well known social media were involved in the explosion of information. But so were face to face conversations and standard phone calls.

I remember that the first information that I received was from my wife who was talking to a friend who had received a text message from another friend relaying information from mobile phone call with her daughter! The message that was relayed was that they were in lock-down at the pool and there was a guy running around with a gun shooting people.

Then I read a Facebook report that the guy had a Nerf-Gun. I synthesized and retweeted those two bits of information and was emailed by a reporter from the O.C. Register who wanted to confirm my update that he saw on Facebook. I, of course, couldn't confirm it as I was just passing along information that I had heard.

Later, a student wearing camouflage was arrested in the student union which was also in lock down at the time. It eventually turned out it was the wrong guy who made an unfortunate fashion choice that morning.

Hours later the information flood settled down and it was revealed that the guy with the gun was a student with a paint-ball gun who was shooting paint balls in the field and was going home. He was mostly oblivious to the craziness going on around him because he wasn't online and he wasn't apprehended in any reasonable amount of time. He eventually apologized profusely for being dumb enough to carry a paint ball gun onto a college campus and being seen.

I had a couple of observations about this event. The first was that the ZotAlert system was very authoritative, and not surprisingly was slower to send out the facts. This was, hopefully, because they were trying to make sure they actually had facts.

Another observation was that the social media was extremely effective at getting out the word that something was going on. The subject and accuracy of the something varied to a great degree. When it comes to a potentially dangerous situation like this could have been I think that this was a success. Even if you can't communicate the right information, you would like everyone to be on guard and in the right frame of mind to respond appropriately when they get first hand information.

Lastly it was interesting to see how much this media space is fractured. Every social media tool I was involved with was lighting up. No tool had a monopoly on the communication. They were each used to individual strengths and to communicate to particular people. It appears that our community has a pretty good sense of which tools different people pay attention to. So when I want to reach my wife I text message, but if I want to reach my department I send an email.

In the paper "Chatter on the Red: What Hazards Threat Reveals about the Social Life of Microblogged Information" by Starbird, Palen, Hughes and Vieweg and published in CSCW 2010, the authors look formally at some of these effects.

Their data source were tweets that were sent out around the time of a 2009 flood in the Red River Valley on the U.S/Canada border. This event lasted for several months, so the nature of the information was much less about being individually safe for the next few hours and much more about being safe as a community for weeks.

They commented on the fractured and heterogenous nature of social media:

"Collection and analysis of large data sets generated from CMC [Computer Mediated Communication] during newsworthy events first reveals an utterly unsurprising observation: that publicly available CMC is heterogeneous and unwieldy. ... Our tweet-by-tweet analysis of the Local- Individual Users Streams indicates that most are broadcasting autobiographical information in narrative form, though many contain elements of commentary and the sharing of higher-level information as well. Even as some Twitterers shift focus to the flood, most continue tweeting within their established Twitter persona."

and although they had contradictory comments about what Twitter was this quote reinforced my view that as a technology, Twitter is an infrastructure for low-bandwidth multicast.

" Twitter, a new incarnation of computer mediated chat, is a platform without formal curation mechanisms for the massive amount of information generated by its (burgeoning) user base. There is no rating or recommendation system support—key features of commerce sites like Amazon and information aggregators like Digg. Nor is there a complex system of validation that, for example, Wikipedia has implemented. Also unlike Wikipedia, content passed through Twitter is short-lived, and therefore cannot be discussed, verified and edited. While most social media have “places” for interaction, interaction in Twitter occurs in and on the data itself, through its distribution, manipulation, and redistribution. Without regular retransmission, communications quickly get lost in the noise and eventually die off."

Another difference between UCI and this flood, was that the time scale allowed people to do more self-organization and to create more digital tools to help manage the information flow than would be normal over the course of hours.

The authors reinforced a belief about geo-located data that I previously blogged about which is that there is nothing about twitter which should make you think that localized data is really more local. It is a means to broadcast and subscribe and what you do on top of that is communicate. Just like all communication it is human centered and not easily parsable by a machine. So the researchers spent a lot of effort curating a set of tweets that were related to the flooding. There was one caveat which I'll mention below

Some interesting facts that emerged from their study were that only about 10% of the tweets that were in the dataset about the floods were original. And of that 10%, it was split between autobiographical narrative format and knowledge introduction. This is the same pattern of use seen in "Is It Really About Me? Message Content in Social Awareness Stream" between Meformers and Informers.

A curious note about this dataset though was that the localized data was three times as likely to be original. This is a reasonable expectation given the dataset but speaks to a place in which the merging of local and localized data does occur.

Those that weren't original were sometimes synthesizing other tweets. This included editing, curating and synthesized the data from others. Then another group of people were posting educational tweets related to the events unfolding.

A final interesting behavior that was observed was the sensor stream to twitter account phenomenon in which some talented folks connected a sensor measuring flood levels to a twitter stream which periodically tweeted data. This is something I would like to explore in much greater depth.

Posted by djp3 at February 26, 2010 9:48 AM | TrackBack (0)