Amazing feats in collaboration (in nature, not technology)

The Atmosphere conference at Google's Mountain View, CA campus this past Monday was exciting and fun and attended by hundreds of interesting CIOs/CEOs and interesting people - there was even a great set of announcements from our own Google Docs team, which was of course a highlight for me. But, whether or not you believe in cloud computing or have any interest in the technology side, if you have any interest in collaboration, you must watch this video from the conference. This presentation by Janine Benyus, the President of the Biomimicry Institute, was, for me, the most educational, intriguing and awe-inspiring presentation of the whole day (yes, even more than seeing several people edit the same doc or drawing at the same time ;).

It turns out, that as much as we think we're innovating in the area of collaboration, we're actually just catching up and still, perhaps, way behind the collaborative systems present in nature.

Is Twitter today's CB Radio? so what...

If you were born after 1975-ish (younger than 35-ish), chances are you won't get this post - but if you were a kid (or a trucker) during the 1960's and 1970's, you might relate. It struck me that the CB radio was basically Twitter - just on a different channel (quite literally) - using audio airwaves rather than the character-based internet. "Citizen Band" (CB) Radios were primarily used by truckers to keep in touch with each other and with a base station - maybe a dispatcher. The CB was their practical tool to communicate. Then, kids and geek hobbyists got a hold of them. I got one as a kid - probably in 1973 - when my dad finally gave in to my persistent begging. My dad certainly made me pay for it - but he risked his life on the ladder to install the antenna... I clearly remember him dropping the antenna once as he almost fell off the ladder. But, even bent, the antenna hooked me up to a world of tweets... voices of other people and truckers with whom I purposelessly interacted (that sound too familiar?).

Then, on a long car ride to Florida, the value of the CB became clear. We took the CB in the car and formed several temporal voice relationships with some truckers on the same route - down i95. On more than one occasion, we were warned of trouble, radar traps, accidents - and the previously useless banter became useful - almost necessary in hindsight.

Some other characteristics of the CB which seem analogous:

• We had "handles" - names that represented who we wanted to be... sometimes fun, sometimes close to our real personas. The only one I remember was my uncle's: StoneMan. You figure it out.
• We had our own language, which I think follows police radio language... like 10:4 ("ok") or 10:20 ("location") or "smokey" (policeman). wow... tricky.
• We had Channels - similar in my mind to #hashtags - but much less traceable.
• Short Tweets... after all, you could only hold that little button on the side of the mic for so long...
• CB's were trendy! (tweet tweet!) There was even a hit song by CW McCall called "Convoy"

This loose analogy between Twitter and the CB radio is not very enlightening, unless you want to believe that Twitter will face the same fate. So what was that fate? I'm guessing that hobbyists found more interesting and extendable platforms (not to mention the Internets ;) and truckers still use the CB in it's original form. If it were searchable, linkable, with more traceable social structures and usage patterns and without any locational limitations, maybe CB radios would have kept growing.... or maybe they did keep growing, right out of that stupid box in my room as a kid and into a chat room, then into that phone in my pocket and then into Twitter.

Maybe someone reading this post will take a hint and help those truckers still using CBs by launching a product that has the familiar, voice-based interface of the CB, but with the added the practical advances of Twitter! Traceable, linkable, bit.ly-able, followable CB Radios! ...
Hmmm.  Maybe not.
10:4 good buddy.

Amazon and Rice - an unexpectedly good recipe

I know Amazon is not just for books, but even I was surprised at this recent purchase made by my "use the web for practical things", non-geek, wife. I came home to find two seemingly unrelated things... First, there were six boxes of our favorite Rice on the counter - previously though to be extinct in this hemisphere due to the fact that our local grocer stopped stocking it. Nice surprise, but where did they come from? Second, there was a medium-sized Amazon box on the floor (you know, in that spot where husband might eventually remove it, but often takes much longer than necessary to do so). "What'd you get?" I innocently asked. "The Rice". The Rice? The Rice came from Amazon.com? whoa.

I know this doesn't constitute a "whoa" if this was a toy or a camera or even a pair of shoes... but Rice?

Logistics and partnerships have quickly made Amazon purchasing one of the most powerful forces in the product distribution space. Any product - even Rice - has a place in Amazon's warehouses and, optionally, on their website. It's been going on for a while - but now that it impacts my grocery list - I'm way impressed. Who cares if my grocer stops carrying stuff? I bet I can just scan all my groceries at home already and... well... you know...
By the way - you MUST try this rice.

You see photo, I see template

I've always been excited about the templates gallery we have on Docs - but over the past few days, I could probably be more aptly described as *crazy* about templates - presentation templates in particular. It's the "submit your own" thing that pulled me in and got me thinking that practically everything around me "would make a great template". And I really like the way the embedded template summary/thumbnail looks in a blog post or on a site - like this:

It started with the billboard...

That was just a cool way to show simple messages, and it seemed like something others could make use of. I suddenly started seeing other things around me which could also be good backdrops for simple message slide shows - like the side of a barn, a laptop screen, or even a mobile phone! I even went through my own photos and started pulling other things out to make into templates - flowers, shells, frogs - anything with some topical relevance.

Here's instructions on how to make your own (using one of my templates, of course):

I'll try to improve that presentation with screenshots and more detail if people ask... but really - the hardest part is finding and editing the right photos... some might say that I failed at that ;)

Twitter search results are more useful in a spreadsheet

I know I've overstayed my welcome in this utterly boring space of Twitter API data in a spreadsheet - but I just have to share one more... This time, it's something that might actually be useful (omg, did I just admit that all the other stuff was useless? uh huh).

Let's say, for example, you are a product manager (hey - i know one of those) and you want to know who is tweeting about your product... You do a twitter search! Cool! It's really easy to see recent tweets about your product. You can page through the results, and, in some tools even see a quick info box on the specific Tweeters listed (like location, number of followers, etc). But - let's say you want to calculate the total "reach" or, as @psychemedia called it in a recent tweet, "amplification" of the tweets which match your search?

"There's an app...err... a spreadsheet for that" !

Here's what this spreadsheet does:

- Pulls the most recent (up to) 400 tweets which match your search terms (there's limits in the twitter search API how far in time that will go back) into the spreadsheet.

- It includes: the tweet text, author, date/time

- For the most recent 50 tweets, it pulls the number of followers for the person who tweeted somethhing that matched your search terms... and it adds those up and give you a "Distribution for the most recent 50 tweets". In other words - the number of people following the people who tweeted about the thing you searched for.

- For the most recent 50 tweets, it filters those which are ReTweets (RT) and sums the followers for the authors of those tweets - giving you a distribution of RTs of that concept or tweeter (this is meant mostly for searching for a tweeter's screen name to see the distribution of RTs of that persons tweets).

This is not rocket science (I realize) - but it forms a basis to allow you to:
> get a sense for the amplification of a specific term or product name or tweeter
> focus on the tweets in a search result set which were authored by highly-followed tweeters (if you are a PR/marketing/customer-service person in particular)
> do further stuff with this data that I haven't thought of or had time to do...

Like the other twitsheets I've done - this is just meant to be a starting point for people with a purpose... so if you come up with something useful from this, let me know!

Twitter says: Coldplay follows the unpopular, Oprah doesn't

Coldplay follows 2,624 tweeters on twitter - who, on average, are only followed by 10 people each. Oprah on the other hand only follows 14 people, who, on average, are followed by 709,350 people (as of this post on 9 June, 2009). I know - I spent the past 14 weeks counting! Nah... actually - there's a cool way to do this in - yes, you guessed it - a spreadsheet.

In tweaking the TweeterScore and other TwitSheets I've discovered that using xpath, you can quickly summarize data from an XML feed into a spreadsheet... that is, you don't have to do the adding and looping yourself.
In one command, you can summarize data across all the entries in any XML feed.
For example... the twitter XML data for "friends statuses" (the recent tweets of all the people you follow) can be grabbed with a URL like this:
http://twitter.com/statuses/friends/whatsername.xml - and you can do that for any tweeter, to see the statuses of (and other stuff about) all the people they follow...

The actual XML data - in brief form - includes something like this (shortened massively):
<users>
  <user>
    <id>1010101</id>
    <name>Whatsher Name</name>
    <screen_name>Whatsername</screen_name>
    ...
    <followers_count>1031</followers_count>
    ...
    <status>
      <created_at>Tue Apr 07 22:52:51 +0000 2009</created_at>
      <id>1234567890</id>
      <text>brb - going to get ice cream now</text>
      <source><a href="http://www.tweetdeck.com/">TweetDeck</a>
      </source>
      ...
    </status>
  </user>
</users>

So - for the given tweeter (that you gave as the tweeter-screen-name.xml file name) it gives information for every other tweeter that person follows. A cool way to get the raw data for every person they follow. But the best part is the ability to summarize across all the entries... and XPath lets you do that.

Example: Let's say I wanted to know not just all the names of the people that Oprah follows (no idea why i picked her) - but I wanted to know the average number of people who follow the people she follows. That would tell me whether Oprah is following her fans (unpopular) or other celebs (popular, with lots of followers themselves).
I can do that in a spreadsheet in one command (almost).

I use the ImportXML() command with an XPath command string of "sum(/users/user/followers_count)" to get the total number of followers of all the people being followed by this tweeter... so for Oprah, the spreadsheet formula looks like this:
=importXML("http://twitter.com/statuses/friends/oprah.xml","sum(/users/user/followers_count)")
Divide that by the number of people she follows, and you have the average...
I'll leave it to you to check out this sample spreadsheet which does a whole bunch of this xml manipulation to compare 10 tweeters.

Show-n-Tell gadget in honor of GoogleIO

Find out more about this gadget... or, If you see nothing above this message, or you just don't get this whole post... please excuse me and move on to your next critical task for today. ;)