Since I first posed the question in April “Has a Twitter emergency alert system been built yet?”, I’ve noted that several other people have pondered the same concept. Some examples are here, here and here.

It has already been substantiated that when an emergency occurs almost anywhere in the world, the first notification of the event occurs online among socially connected individuals using systems like Twitter.

Social groups of loosely aggregated individuals with similar interests, microcrowds as I’ve been calling them, or groupings as Stowe Boyd calls them, seem like an ideal communication channel for use in emergency situations. Microcrowds overlap and each have “pack leaders” or “social seeds” with deep downstream social connections in the form of followers or friends. The leaders in these groups are generally highly connected through the use of communication hardware like WAP phones and laptops with EVDO connections so highly important information can flow through the #microcrowd channel in near real-time.

If Chris Messina’s concept of #hashmarks as an impromptu channel creation methodology is adopted in Twitter, then perhaps this can also be used to create a repeater system that binds together the alpha leaders of the largest social groupings and emergency response teams, thereby using the massive redundancy of social nets to ensure that important messages are broadcast far and wide.

Adding geo-context to the emergency message would be an important aspect to consider. Temporal-context would also need to be applied so that as the message ages, additional information and updates can be properly contextualized along the timeline of the disaster.

As our dated analog systems fall further behind the power and immediacy of social communication perhaps it’s time to propose an emergency social-repeater system, where emergency information can not only flow quickly, but flow to the people and systems which can possibly affect the speed of response teams and mitigate the negative effects of any disaster.

I learned a new word the other day, Captology, and it helps me define an area of thought of particular interest (thanks to my buddy Crosby!) I was talking with him about some of my recent posts covering geo-temporal and microcrowd concepts and he suggested that I check out a particular Stanford University website. According to the description on the Stanford University Persuasive Technology Lab website, the definition of Captology:

Captology is the study of computers as persuasive technologies. This includes the design, research, and analysis of interactive computing products created for the purpose of changing people’s attitudes or behaviors.

And they have a nifty Venn diagram that I’ve borrowed so you can visualize the concept.

At the moment I’m thinking of how captology interacts with microcrowds. Specifically microcrowds on Websites, Mobile Devices (iPhone), the desktop, in Virtual Reality (SL), and where this crosses over into in-person interactions with geo-temporal implications.

Definition of Microcrowd (s): noun. A group of people in which members are passive, active or aggressive participants. A Microcrowd member may influence other members with their participation.

Example: When I saw my acquaintance Justin Kan during a Citizen Agency party the other day, our discussion led me to consider some new thoughts about geo-temporal tracking. Justin has no idea, but the conversation and my active participation within a specific microcrowd of people altered some of my evolving thoughts around this type of tracking.

In addition to interacting with this example group in person, I also interact with many specific members online. Twitter, chat, email, blog comments and many more points of distributed contact form my networks within the microcrowds that I interact with. Blackberry and MacBook Pro are my primary connection tools, but within email the browser and other applications I also connect with asynchronous video (live: justin.tv recorded:viddler.com) and more.

I might log into the justin.tv website in order to “watch the content”, but because he lives in my city I might log in to see where he is, or to see if the party I’m going to is worth getting into a cab for (Justin tends to hit the same party scene I do so I can “preview reality”.) This seems like the ultimate in technology impacting me, influencing my decisions, yet this decision is also influenced by the wisdom of the microcrowds because if I didn’t travel a similar SF party circuit as Justin and could not “preview the party” then my party-going decision making would be influenced by other microcrowds. If I find out that the Extra Action Marching Band will be at the party, my passive participation in the microcrowd centered on this band would tip me towards attending the party, even without a “reality preview” through Justin.tv, because I love watching this band. Knowledge of their attendance tipped me into going. Once I’ve made this decision, I might Twitter or email about the party to get friends from my other microcrowds to attend. And so it spreads.

At the Citizen Agency party I might have learned something that changes important parts of my life, or I might learn somebody had a birthday. At a Giants baseball game I might be influenced to care more that someone had just hit a homerun, or I may learn that someone that I know had a heart attack. The information conveyed is not important to this particular post as I’m focused on how information waves spread through and among microcrowds. How the information is relayed and the influence applied from within the community and the technology that is in the hands of community members during the conveyance of the message is important, impacting persuasion and human behavior.

I’m participating in many microcrowds in many different ways; in blogs, with family, on social websites, at parties and general assembly events, on handheld devices, in school, on music and video players. Each touch point that I have with the technology tools or in face-to-face meetings will generally influence what I think about and how I perceive “it”.

This appears to be like memes moving virally towards a tipping point, but I believe it’s also analogous to neuron pathway development, influenced by the volume and type of connectivity and communication of participation.

This post has been languishing in my drafts folder for some time, so rather than sit on it longer, or draw any conclusions, I’m just going to put it out there for discussion … hopefully this spurs some new ideas for you.

Even laundry rooms, like this one at Olin College Twitter now, so are you still waiting to create your own Twitter account?

When two washers, two dryers and a condom machine create content autonomously, broadcasting to the world their temporal status, available, unavailable, I smile because we are finally beginning to see a very granular point of view with web content.

Twitter is about “now” time statements. So LaundryRoom needs to continually ping their followers with updates, but they only ping when the status of a machine changes. The machine has a location that must be described in order to find it and the moment in time in which the machine status changes is important because as everyone knows, washing and drying machines are quite popular in large buildings full of students and you need to be on the ball to get a machine before others do. In this regard, Twitter is a great system to connect with a Laundry Room and a group of student followers.

Micro content regarding the status of machines is beginning to show up everywhere, from parking meters to washing machines, so why are humans so slow to adopt a more systematic organizational structure for geo-temporal tagging their own lives? We tag here and we tag there, and some systems add meta data for us, but overall we don’t yet use a uniform system for tagging our daily interactions with technology on a geo-temporal basis. The reason why this is such an important point to understand is because by adding Time and Place to our electronic trails, we can access our personal history and share what we learned on the journey. We might also pull other real or virtual people into conversations if we enable others to see where we are, when we are there. If my phone broadcasts my GPS signal and tells my friends automatically “hey, come visit me at this location”, even if I’m in a virtual world like SecondLife, the possibilities created are interesting to ponder.

So where Dodgeball has mostly failed to live up to the concept, perhaps other newer, simpler, more automated systems of geo-temporal “shouting” which work at a more fundamental web standards level, can gain some traction in the market and help us all connect more. Or we might simply want to wash our clothes and need to know when a machine is available in our dorm without interrupting our PS3 gaming to walk down the hall. I’d like to reserve the next available open machine….. Thanks Twitter.