Summary:

Fashionista is concept work I did in 2007 for a mobile social networking company in Australia on based on some observations on teen cell phone use. This work pre-dated the iPhone, twitter but still seems relevant.

The Inspiration:

In communities in which unlimited text messaging is common, it’s not atypical to see some users send between 100 to 200 text messages a day and certain heavy users regularly top 1000 text messages, an average of 1 message every minute. The majority of these messages are being sent to, at most, 5 or 6 of their closest friends. What is the content of these messages and how do we explain this behavior?

Peaks and Heartbeats:

If you were the draw a graph of the level of “excitement” that you experience over the course of a fortnight, it might look something like this:

Among the course of your life would be a series of peak experiences, experiences that are in some way out of the ordinary. So far, social networking sites have been primarily oriented towards the sharing of peak experiences but peak experiences does not explain the heavy texting patterns of teens. There simply aren’t enough peak experiences to fill up that amount of content. Underneath the peak experiences is what I call the heartbeat of your life. The heartbeat is the regular, periodic patterns that make up the bulk of your life. While this heartbeat is somewhat predictable and mundane, it also contains variation and what I call “texture”. Every day you might have lunch but you have something different each day. Every week you might go shopping but you buy different groceries on every trip. The texture of your heartbeat is information that is too mundane, even for Facebook. The texture of the heartbeat only makes sense when viewed in context: that I had a banana for lunch today is only interesting to those who know what I’ve had for lunch every other day of the week. As such, connecting and sharing your heartbeat is something that is done only between close and intimidate friends. It is this heartbeat that explains the communication patterns of teens. Each text message alone doesn’t convey much information but the aggregate of hundreds of messages over a day give teens a finely nuanced perspective unavailable through any other communication medium.

Exploiting the heartbeat:

Mobile social networks are uniquely positioned to capture this heartbeat data and take it to the next level. But for this to happen, they need to support the structure that puts such heartbeat data within a context. Fashionista is a tool for highly fashion aware women to show their friends what they’re wearing right now. Every morning, a fashionista user wakes up and decides what to wear, how to style her hair and how to accessorize herself. Once that’s complete, she takes a photo of herself in the mirror with fashionista and this image is automatically beamed to her close circle of friends. Over breakfast, she receives constant updates from what her friends are wearing that day as well as comments from her friends about how much they love the boots she’s wearing. Later, as she’s planning her social activities for the evening, she receives another pulse of notifications, keeping her in touch with what her friends will be wearing. Each notification conveys the subtle rhythms of the day. Not only what are you wearing but what time did you wake up? What does your facial expression tell me about your mood? Where are you going to be tonight and how do you feel about it?

Conclusion:

Mobile social software is still largely an unexplored space. We are currently in the phase of translating desktop style interaction onto the phone but very few truly native phone apps exist. One new ability that the phone opens up is this ability to share the heartbeat and Fashionista represents a class of apps that could have only been built on the phone.

Addendum:

Since 2007, the mobile landscape has changed significantly. The iPhone has redefined mobile software and twitter has gone mainstream and several highly innovative mobile applications have gained widespread success. Yet the few attempts at mobile social networking still try and replicate the desktop model of sharing. Twitter is probably the closest to hooking into the heartbeat but it’s still not there as it doesn’t have the appropriate privacy controls to segregate content meant for close friends from those meant for strangers. I’m excited about push coming to the iPhone as I think this will be the turning point for heartbeat apps. Heartbeat apps, by definition reside in the periphery rather than the center of attention. They need to be glanceable and the content needs to be absorbed effortlessly. The ideal solution would be for Apple to open an API to control the home screen but push, if implemented right would get it half of the way there.

Responses

  1. Ross Lee Graham, PhD says:

    September 4th, 2011 at 6:48 pm (#)

    It seems to me a much easier to simply read “The Little Prince” and apply what you learn there. Pay especial attention to the conversation between the fox and the Little Prince on friendship. Reductionism tends to be most effective in these matters if these matters can be reduced to an algorithm, which is to say rendered mechanical. The thought that friendships can actually generate from an algorithm and hence be mechanical seems to be the logic of a politician who thinks the public is always fooled by this form of posturing. The foundations of friendship are not based on logic but rather from the heartfelt intuitions. This is why when people try to form friendships through writing to each other they spend much time trying to read between the lines (so to speak). So far no one has discovered an algorithm that ‘reads between the lines’, which is another way of saying that no program for this activity has yet been developed. It is quite another thing to develop a mutual respect among colleagues of similar professions, yet even here there is effort to read between the lines. No one has yet succeeded in eliminating the role of intuition in the formation of friendships, which is to say we have yet to find an algorithm that generates intuition.

  2. Ross Lee Graham, PhD says:

    September 4th, 2011 at 9:03 pm (#)

    Somehow my previous comment, which references ‘Le Petit Prince’ ended up in the wrong place. It was supposed to be with the failed program on making friends etc…

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    February 16th, 2012 at 4:44 am (#)

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