Monthly Archives: October 2009

Twitter and conversation analysis – who’s here?

“Hoosier,” the somewhat odd name for a native from Indiana, may have its roots in conversation. One of the stories is that when a knock from someone at the door rang out, the person inside would ask, “Who’s here?” and the greeting was shortened to “Hoosier?” Since I grew up in northern Indiana, my memories of it are fond and nostalgic. I’m particularly pleased that some of the researchers of Twitter and conversation analysis are at Indiana University, a lovely campus that I visited more than a few times.

Is Twitter appropriate for conversation and collaboration?

Tonight I’m reading a paper titled “Beyond Microblogging: Conversation and Collaboration via Twitter” originally published in the proceedings for Hawai’i International Conference on System Sciences. Written by Indiana University professor Susan Herring and doctoral candidate Courtenay Honeycutt, it describes some research questions about Twitter being used for conversation and collaboration. To quote from their discussion, “This study investigated the conversationality of Twitter, with special attention to the role played by the @ sign.”

Specifically they studied the public timeline and the use of the @ symbol that Twitter users actually invented to talk to each other as described in this New York Times article, Twitter Serves Up Ideas from its Followers. The researchers also had to filter out the other uses of the symbol, some of which are entertaining. The emoticon @_@ is one googly-eyed guy that they didn’t intend for this study. The offhand reference to someone else using the @ symbol was also filtered out, along with email addresses, and location references such as “I’m @ the coffeeshop right now.” They wanted to study one Twitter user addressing another for specific reasons.

They found that the @ sign use has doubled in two year’s time, and that Japanese and Spanish speakers use it as often as English speakers.

How is the user-invented @ convention changing conversation-based content?

They also found, and this was interesting to me, that the use of the @ symbol may actually be expanding the types of content that are being used in microblogging.

We further found that tweets with @ exhibited a
wider range of content, in comparison to tweets without
@, and that most tweets without @ just answered
the Twitter site’s question: What are you doing? This
suggests that @, in addition to directly enabling a more
interactive use of Twitter, is indirectly contributing to
expanding the types of content expressed in tweets.

In the footnotes they further note the use of the @ symbol to address others is happening in Flickr, the photo sharing site, and I would add that it’s also used often in blog comments when responding to a specific person. It’s spreading as a standard, practically! Updated to add: right after publishing this post, I hopped over to Google Wave, and in a non-profit wave I joined, they had already implemented an automatic link to a person’s Twitter account if you addressed them starting with the @ symbol. Woah.

Learning more about conversation analysis

Last month I spoke with Tanya Rabourn, who is studying information science at the University of Texas who helped me begin to understand conversation analysis. She said that studying Twitter is “sexy” right now, but also pointed out that research in conversation analysis originated with studying suicide hotlines for conversation patterns. Yow. Conversations on IRC are also studied frequently – text based conversations are easily enumerated and analyzed, I suppose. There’s even a tool available for download from Indiana University called VisualDTA that helps with Dynamic Topic Analysis (DTA) by providing a way to visualize the structure of the topic flow within a conversation. (See pages 7 and 8 of the Beyond Microblogging: Conversation and Collaboration via Twitter PDF for examples of VisualDTA diagrams.) I also learned a lot by reading a blog entry that describes written discourse at Studying online conversation in the Twitter generation that Tanya had tagged on a social bookmarking site. I learned that Conversation Analysis studies the “norms and conventions that speakers use in interaction to establish communicative understandings.”

Customer support and Twitter

Naturally, seeing how I’ve written a book with Conversation in the title, I want to relate what I’m reading to what I’ve already written. (Or is that unnatural?) So, where are the customer support conversation analyses? Has anyone studied the back-and-forth written discourse that occurs in 140-characters to see what some best practices are for engagement and troubleshooting to help someone with Twitter? Or is Twitter simply a method to get to the front of the support queue by saying “Pay attention to me because I have a smart mobile device so I must have a bit more money than your average slob of a customer!”

I believe that phone conversations for customer support have been studied quite a bit – looking for phrases that sound like triggers for anger, avoiding long pauses, and when one party overtakes a phone conversation, it’s relatively easy to detect when that’s happening. But with Twitter, you could have long pauses intentionally as asynchronous, IM-like conversations happen when someone gets up from their desk and returns after a business meeting, for example. Neither party is angry about that long pause, it’s just an understood agreement in the Twitter medium that you may or may not be immediately responsive. How does that time factor change the “agreement” for a support exchange? Is Twitter reserved for the narcissistic whiners? Or are true relationships happening and caring, meaningful attention being paid to customers on Twitter?

Wait, don’t answer these questions. I want some data and dynamic topic analysis to back up your theory. 🙂

DITA tools wiki writing

Notes from WebWorks RoundUp 2009

I attended two days of the WebWorks Roundup here in Austin this week and served on a few panels. I enjoyed signing books as every attendee got copies of books from XML Press. It had featured speakers like Tom Johnson and Stewart Mader as well as sessions with Lisa Dyer and Alan Porter to name a few. Here are my summary take aways from the sessions.

Wiki adoption

Stewart Mader is a wiki consultant, probably the most experienced, practical, and sensible wiki adoption expert available today. His message about wiki adoption resonated with me as I look for collaborative authoring solutions for our Agile teams. He said, if you look around the enterprise, people have high adoption of email for their daily business tasks. In the adoption phase for a wiki or collaboration system, you can tie a wiki to email conceptually as this ubiquitous useful way to get work done. If you think about it, more complex systems have a higher learning curve, so people default back to email to get into their comfort zone. But, sending email messages is an isolating experience – email doesn’t let you work together collectively like a wiki does.

For example, working in the shared space of a wiki is like using light rail to get to work. He has made friends on the train he took each day years ago and he’s still friends with them today. In other words, being in an environment that enables social interaction is more powerful. He says to think about the business process a wiki affects – do not just apply what the Internet says to do with a wiki. The biggest and most powerful collaboration going on with wikis in the enterprise is group collaboration – small groups. You don’t want one-off contributions once, you want repeated collaboration and repeated use, as frequent as email and as a simple core tool that they use for everyday business. Preach it, brother!

He also talked about measurements to indicate that adoption is successful. One of the biggest dangers he sees is counting the number of pages created when adopting a wiki. Don’t do it! Better metrics are measure per time period or per some other unit:

Views                    Day
Revisions      per       Page
Comments                 Unit
Tags                     Type

Automation – 1001 Nightly Builds

Some of WebWorks’ customers gave talks and a panel discussion about automating software builds using WebWorks Automap. These were great eye-openers and my ears perked up because they were writers working in Agile environments. They have to release in tandem with internal development cycles, so they automated as much as they could. One doc group used to have a 15 page document on how to create a PDF complete with screenshots for all the settings. Mary Anthony from Palantir said their writers have to document 4 user interfaces, 3 admin GUIs, more than 12 servers and an API, and they used advanced techniques such as text insets in FrameMaker. Using WebWorks, another writing group had automated PDF generation, wiki output, plus HTML output, all from Framemaker source files.

This was interesting to me – they found there was a true documentation domain and it was hard for someone who usually builds software for them to put together docs. Terms like cross references, text inserts, and so on, were foreign to their build engineers. They don’t even have the concept of “book” as a collection of chapters with a TOC in Framemaker. Even using a Windows server to automate builds was outside of the build engineer’s knowledge.

I learned about a tool called Apache Ivy, which is an agile dependency manager. Using this manager helped them integrate their documentation builds with the product builds. Mary Anthony explained that Ivy waits for the outcome of another build – like a refrigerator holding chocolate pudding, Ivy opens the fridge door and gives the build process what it wants (the chocolate pudding, or the fine documentation).

Overall a great couple of presentations about automation from which I learned a lot.

Blogging and Web 2.0

Tom Johnson is a blogger and technical writer and likely the most subscribed-to blogger in our particular tech comm niche. He gave a great talk based on his blog series, Seven Deadly Sins of Blogging. In case you’re curious, the sins are being Fake, Irrelevant, Boring, Unreadable, Irresponsible, Unfindable, Inattentive. (I’ll link to the rest once he has the blog posts finished.)

He had great pictures representing each sin. My favorite quotes were from Penelope Trunk (The Brazen Careerist, Blogs without topics are a waste of time) and Stephen Fry’s blog entry, “Don’t Quote Me“.

This session was a great starting point for our next panel about Web 2.0, although we mostly talked about blogging. The Technorati State of the Blogsphere 2009 report came out yesterday, so it was useful to talk about some of the findings from it (73% of bloggers use Twitter as compared to 14% of the general population, for one.) I enjoyed talking with Alan Porter and Tom on this panel and I may have asked as many questions as I answered. All in all, a great two days of discussion and presentations.

How you learn to use Google Wave

Since I write user assistance for a living, I’m naturally drawn to the devices the Google Wave team is implementing in order to teach people how to use Google Wave.

For me, there were a few waves in my inbox from the start. First, Doctor Wave, impersonating a Bill Nye the Science Guy character appears in the “Welcome to Google Wave” wave as an embedded YouTube video, and points to different areas on the screen while embedded in a Wave. It’s a nice welcome and a great navigation aid to the user interface, very clever in that the perspective is as if he’s talking to you from the inside of the interface. I liked it despite my normal reluctance to take two minutes and twelve seconds to watch a video about something I need to understand better. The video won’t be nearly as effective outside of the Wave, but you could still learn from it if you view it in YouTube instead of in the Wave.

doctorwaveFrom embedded video to try-and-see to blog entries

Next I started clicking around, and was naturally drawn to my Contacts to see who else is on this invitation-only site? The ones pulled from my Gmail contacts were nearly all from OLPC, since that account is my main email account for that project.wavefaq

After that, nearly all of my learning process came from Mashable’s blog entry titled Google Wave Guide, and videos about using Google Wave. I also studied their entry titled “Testing Google Wave: This Thing is Tidal” before getting my invite. One of the best “getting started” guides is also by Mashable. Wow, how did Google get third-parties to write their Getting Started Guide? 😉 In reality, the Mashable blog entry also serves as a map to the Google help itself, by pointing to the list of Advanced Search terms for Google Wave, for example.

Only after logging on for another two or three times did I find a Google Wave FAQ, written as a wave. I think this FAQ is a great example of documentation when you need it, simplified and task-oriented.

Mostly I am learning by exploring. Last night, Char James-Tanny set up a public Google Wave for STC, the Society for Technical Communication, called STCWave. I found it by searching for “with:public STCWave”. By using that Wave I was able to add more technical communicators to my contacts list, especially those that I didn’t have a Gmail address for previously.

Agile team collaboration tool

I have to wonder aloud if Google built Wave as an essential part of their development teams’ collaboration arsenal. Real-time collaboration is so important to being successful at Agile. Having searchable archives of team decisions and team discussion can be extremely helpful, and photo and document sharing can help a team “gel” so well. We’ve been using Etherpad and Campfire for text-based discussions and some file sharing as well as shared document editing.

Search integration

I have also found it essential to know some basic search phrases to help you find Waves that will be useful to you. One is “with:public” (no space after the colon). With that search delimiter you can find all Waves with public users invited, and other user names and group names can be substituted for public. You can search based on participants, creators, the state of the wave (such as read, filed, and muted), and the types of attachments in the Wave.

Being a student of the Wave

So what are the best ways to learn Google Wave? I think that conversational and community teachings are the way of the Wave. Text is still a huge part of learning, yet printed artifacts are not (yet) a part of learning Google Wave. Video and screencasts are proving to be made by many people.

And finally, learning by experimentation is how many of us will learn Google Wave, especially since its access is to a limited release and invite- or nomination-only web application.

Update – The Complete Guide to Google Wave is now available. A purchase of the print copy goes to a great cause.

Content curation – a manifesto

The phrase “content curator” was one I had to define in the glossary of my book. It seems now that content curator is an idea that others are writing about as well.

RJ Jacquez, Adobe product evangelist, tweeted a link to an article about Content Curation on the site Social Media Today titled “Manifesto for the Content Curator,” written By Rohit Bhargrava. In it, he describes his definition of a content curator: “A Content Curator is someone who continually finds, groups, organizes and shares the best and most relevant content on a specific issue online.”

manifestoflickrPhoto courtesy ingorr on flickr

I think that professional writers and technical writers should consider a move towards this role. We already search for and find the best content, sift through loads of content, discard poor content, and publish the most worthy content whenever a software release goes out. This description also sounds like something a content strategist would do as part of their analysis of the content.

What I found fascinating after the article had been out a few days was to read one of the comments, where the commentor seemed to think that tasks related to content curation should be automated. He referenced two sites that curate content by classifying it and rating it, and He saw content curation as a great opportunity for software developers and entrepreneurs.

What do you think? I’m guessing my blog’s audience would protest mightily. Do you believe that content curation can be done by algorithms of rating and relevancy? Or should this job be reserved for specialists?