Words and Reputation

Over at the Blue Oxen blog, I wrote about how I’ve incorporated Contextual Authority Tagging (your reputation in context) into my work.    (N5Z)

In the piece, I started using myself as an example. I listed three words that I would use to describe myself in a work context. I then started to contrast this with words that my colleagues might use to describe me. Then I stopped, thinking, “Why make up words that others might use to describe me, when I can get actual words?”    (N60)

Enter Twitter (and by extension, Facebook):    (N61)

Please help with an ad hoc experiment. Reply with three words that describe me. Will blog an explanation and the results.    (N62)

In retrospect, it was an incredibly self-indulgent thing to do. When I do this exercise with groups, it’s anonymous, and all of the participants are doing it for everyone. Neither was true in this case. No one was going to voluntarily say something critical for me, especially without understanding the purpose. Furthermore, I’m usually doing the exercise in a specific context, which is a big part of the point. The beauty (and challenge) of Twitter and Facebook is that my networks there cross all sorts of boundaries.    (N63)

All that said, the exercise was still instructive in many ways:    (N64)

https://i0.wp.com/farm4.static.flickr.com/3340/3490759097_e700bbd3a2.jpg?w=700    (N65)

Most words were only used once. The larger words were repeated one other time. This distribution makes sense, given the multiple contexts of my friends and colleagues. One of my friends wrote, barbecue, something that most of my colleagues probably don’t know about me. A few of my colleagues wrote, wiki, which probably wouldn’t come up first for most of my personal friends.    (N66)

No one repeated any of my words, which surprised me. (Can you guess which three words were mine? See my other post for the answer.) The words that folks did choose certainly paint a fuller picture.    (N67)

I love how a few words can tell a rich story. Gabe Wachob contributed “Eugene Lee doppelganger,” is a reference to the parallel lives that Eugene Lee, the CEO of Socialtext, and I seem to lead. (I’m younger, but Eugene has more hair.) My friend, Elizabeth, wrote, “wicked scary smaht,” an oblique reference to our shared ties to the Boston area.    (N68)

Eugene Chan wrote, “curious, competitive, cunning,” a few days after I talked trash with his six year old son in a vicious game of Uno. The good folks at WikiHowl called me “myopic,” hopefully a reference to my eyesight and not my vision. (They are also my new favorites for calling me, “cute.”)    (N69)

Which brings me to my final point. There were a few cheeky comments (Cindy and Scott, that means you!), which made me laugh, and there were a lot of incredibly nice comments, which… well, which felt good. I’m a fairly well-balanced individual with a strong sense of self (“confident” was one of the words that was repeated), and I don’t need to hear this stuff to know that my friends and colleagues care about me. Still, it’s nice to hear. It made my day that much better. And that’s probably the greatest thing about the exercise. If at worst, all it does is elicit a few nice comments from your peers, well, that’s a great thing. We don’t do that often enough.    (N6A)

Many thanks to all of you!    (N6B)

Wiki Coaching

Today, Blue Oxen Associates launched a new Sensemaking Series on Wikis, coached by Peter Kaminski. It’s a fantastic way to get guidance on implementing and integrating Wikis into your organization, which is even more critical these days, given the economy.    (N5T)

I’m particularly pleased that Pete is our coach. Those of you in the Wiki community already know him for his leadership — not just in co-founding the very first Wiki company, Socialtext, but for helping to drive the community overall with his thinking and goodwill. If you’re looking for guidance, you’re not going to find anyone better or more friendly than Pete.    (N5U)

The series starts on May 19. There are only five spots, so register now. Use the discount code “eekim” to get $50 off registration.    (N5V)

FLOSS Usability Sprint Seeking Great Usability Practitioners

FLOSS Usability Sprint V is happening November 2-4, 2007 at Google in Mountain View. This one is special for a number of reasons. First, it’s the fifth one. Second, our project list is once again superb, including Firefox, Chandler, Socialtext, and WiserEarth. Third, it’s the first sprint being primarily organized by members of this burgeoning community: Daniel Schwartz and Jon Slenk.    (MO7)

The goal of these sprints is simple: Make Open Source software more usable, focusing especially on software for social benefit. Our approach is to bring catalyze collaboration between the usability and open source communities. The sprint takes place over three full days (November 2-4). It’s fun, it’s intense, and it’s gratifying. It’s a fantastic way to meet and work with an amazing group of people.    (MO8)

This sprint is shaping up to be really outstanding. We’re still looking for a few great usability practitioners to participate, so if you’d like to help some socially-oriented Open Source projects in a concrete way, please sign up. And please spread the word!    (MO9)

March Conferences

This weekend, we’re having our fourth FLOSS Usability Sprint, once again sponsored by the good folks at Google. Participating projects will include Mozilla, WiserEarth, Social Source Commons, and Drupal! It should be a fantastic event, and we still have some slots for usability folks, so if you’d like to participate, please apply by the end of the day today.    (LYO)

Tonight is another installment of WikiWednesday at Socialtext‘s offices in Palo Alto. Bryan Pendleton of Xerox PARC will be discussing his research on conflict resolution and coordination on Wikipedia. I had a chance to talk briefly with him about his work last month, and his talk should be absolutely fascinating.    (LYP)

Finally, there’s going to be an unprecedented gathering of folks in the facilitation, Organizational Design, and collaboration community on March 21-23 called Nexus for Change. It will be held at Bowling Green State University in Bowling Green, Ohio (near Detroit). If you’re interested in catalyzing transformation in your organization and in society via collaboration, this is the place to be. I am tremendously bummed that I’m going to have to miss it. I did everything I could to rearrange my schedule, and it just wasn’t to be. Many of my colleagues and friends will be there, as well as some of the deepest thinkers and practitioners in the business. I highly recommend it to everyone, but I’d like to make a special pitch to those of you in the Collaborative Tools business to attend. Should be a tremendous event.    (LYQ)

Visualizing Wiki Life Cycles

On the first day of WikiSym in Denmark last August, I spotted Alex Schroeder before the workshop began and went over to say hello. Pleasantries naturally evolved into a discussion about Purple Numbers. (Yes, I’ve got problems.) Alex suggested that unique node identifiers were more trouble than they were worth, because in practice, nodes that you wanted to link to were static. Me being me, my response was, “Let’s look at the numbers.” Alex being Alex, he went off and did the measurements right away for Community Wiki, and he did some followup measurements based on further discussions after the conference.    (LSP)

As it turned out, the numbers didn’t tell us anything useful, but our discussions firmly implanted some ideas in my head about Wiki decay rates — the time it takes for information in a Wiki page to stop being useful.    (LSQ)

I had toyed with this concept before. A few years ago, I came up with the idea of changing the background color of a page to correspond to the age of the page. A stale page would be yellowed; an active page would be bright white. I had originally envisioned the color to be based on number of edits. However, I realized this past week that I was mixing up my metaphors. There have been a few studies indicating a strong correlation between frequent edits and content quality, so it makes sense to indicate edit frequencies ambiently. However, just because content has not been edited recently does not mean the information itself is stale. You need to account for how often the page is accessed as well.    (LSR)

(At the Wikithon last week, Kirsten Jones implemented the page coloring idea. She came up with a metric that combined edits and accesses, which she will hopefully document on the Wiki soon! It’s cool, and it should be easy to deploy and study. Ingy dot Net suggested that the page should become moldy, a suggestion I fully endorse.)    (LSS)

This past Sunday, I had brunch with the Socialtext Bloomington Boys. Naturally, pleasantries evolved into Matthew and me continuing along our Wiki Analytics track, this time with help from Shawn Devlin and Matt Liggett. We broke Wiki behavior into a number of different archetypes, then brainstormed ways to visually represent the behavior of each of these types. We came up with this:    (LST)

https://i2.wp.com/farm1.static.flickr.com/149/388587151_3f730b0a5c_m.jpg?w=700    (LSU)

The x-axis represents time. The blue line is accesses; the green line is edits. Edits are normalized (edits per view) so that, under normal circumstances, the green line will always be below the blue (because users will usually access a page before editing it). The exception is when software is interacting with the Wiki more than people. The whole graph should consist of a representative time-slice in that Wiki’s lifespan.    (LSV)

The red line indicates the median “death” rate of Wiki pages. After much haggling, we decided that the way to measure page death was to determine the amount of time it takes for a page to reach some zero-level of accesses. We’ll need to look at actual data to see what the baseline should be and whether this is a useful measurement.    (LSW)

The red line helps distinguish between archetypes that may have the same access/edit ratio and curve. For example, on the upper left, you see idealized Wiki behavior. Number of edits are close to number of accesses, both of which are relatively constant across the entire Wiki over time. Because it’s a healthy Wiki, you’ve got a healthy page death rate.    (LSX)

On the upper right, you see a Wiki that is used for process support. A good example of this is a Wiki used to support a software development process. At the beginning of the process, people might be capturing user stories and requirements. Later in the process, they might be capturing bugs. Once a cycle is complete, those pages rapidly become stale as the team creates new pages to support a new cycle. The death line in this case is much shorter than it is for the idealized Wiki.    (LSY)

Again, one use of the Wiki isn’t better than the other. They’re both good in that they’re both augmenting human processes. The purpose of the visualization is to help identify the archetypes so that you can adjust your facilitation practices and tools to best support these behaviors.    (LSZ)

This is all theory at this point. We need to crunch on some real data. I’d love to see others take these ideas and run with them as well.    (LT0)