Last night I watched Carl Malamud’s fascinating, inspiring, and informative WWW2010 address in which he discussed his 10 Rules for Radicals, a strategy for working with (or against) bureaucracies. I won’t summarize here; watch the video.
Nick Carr wrote a post a couple of days ago about the distracting effects of hypertext anchors when reading text. He referred to the increased cognitive effort that in-line anchors impose on readers, but as Mark Bernstein points out, the cognitive effort article was published in the 1980s, and these claims were not supported in further hypertext research.
Patricia Wright’s work on cognitive prostheses suggests that hiding information behind links made it less likely that people would use that information compared to showing it directly. Her argument (presented as a keynote address at Hypertext ’91) is that the cognitive overhead of link following makes people less likely to follow links, not that the presence of link anchors is distracting. Of course the implication is that the further from their context you move the anchors, the less likely that people will follow them. This is the point that Daniel Tunkelang makes in his response to Nick’s post.
The importance of understanding people’s activity to inform design is one of the central tenets of HCI. When design is grounded in actual work practice, it is much more likely to produce artifacts that fit with the way people work and the way they think. One key challenge when studying people for the purpose of informing design is to understand what aspects of existing work practice are essential to the work and what aspects are side-effects of existing technology (or lack thereof) and are fair game for innovation.
While HCIR research often relies on recall and precision measures to compare systems, qualitative methods are used as well. For example, Vakkari and his colleagues studied several students performing research for their Master’s thesis work. Researchers used a variety of techniques including diary entries and interviews to assess the evolution of searchers’ behavior over the course of a few months. Their findings led them to fill in some of the details of Kuhlthau’s model of information seeking.
Happy to note that our overview paper on the Virtual Factory work, “The Virtual Chocolate Factory: Building a mixed-reality system for industry” has been accepted at IEEE’s ICME 2010. The conference is in Singapore in July; I’ll be there, co-chairing a session there that focuses on workplace use of virtual realities, augmented reality, and telepresence. You can see more on the Virtual Factory work here.
Having stumbled onto the IR Museum on the SIGIR web site, I decided to investigate why I had not come across it before. I missed the SIGIR announcement about the museum when it was made in 2008, and since that item was no longer on the first page of the web site, I didn’t find it by browsing. Site search might have helped, but there wasn’t any.
So I tried searching the web.
The University of Washington was one of several universities participating in Amazon’s pilot study of the Kindle DX to see whether the Kindle DX served as a suitable replacement for students’ textbooks. About 40 CSE students enrolled in a dozen Computer Science courses participated in the study. A number of articles published last summer (e.g., Forbes ) touted the advantages of the device for students, citing lower weight and cost compared to the paper editions of the same textbooks.
The results, unsurprisingly, were disappointing.
Thanks to Fernando’s post on Probably Irrelevant, I discovered the IR Museum, an interesting resource hosted on the SIGIR web site. The site was created to archive documents related to the IR community that are not found in the ACM Digital Library or other similar archives, and yet, are considered fundamental work to the field. The collection, as far as I can tell, includes the Cranfield reports (Cleverdon, 1962), Rocchio’s PhD Thesis (Rocchio, 1966), a variety of SMART reports (ISR-11, ISR-12, ISR-13, and ISR-15), and other things that are impossible to find.
A couple of weeks ago I wrote about iAnnotate, a document annotation app for the iPad. On Friday, the folks who develop the app left a comment on the blog enumerating some of the changes made to program. In addition to redesigning the document view, the most significant change made it easier to import documents. Now not only can you download documents through a dedicated server that you run on the network (I run it on my laptop) but also from an integrated web browser. This makes it easy to collect PDF files and then to switch back to the reading mode of iAnnotate to read the newly-downloaded documents.
I was intending to write a post on the varied reasons mathematicians give for taking long walks as an aid to research. I couldn’t find my favorite quote, so instead I’m posting a search challenge.
I thought I remembered reading, in the book Littlewood’s Miscellany, something along the lines of the following advice:
Researchers spend the vast majority of their time feeling frustrated. To improve the ratio of time feeling fulfilled to time feeling frustrated, whenever you find a new result or succeed in completing a proof, take the time to enjoy it, preferably by taking a long walk. Definitely don’t dive into the next problem, or go back and check the proof. There is plenty of time for that later.
However, it doesn’t seem to be in that book. Littlewood certainly approved of walking, and the tone of much of his advice is consistent with this quote, but this particular piece of advice doesn’t appear to be there. I couldn’t find it in a web search either.
I would love to know the true source for this piece of wisdom.
A Tcho chocolate bar to anyone who can track down the source!
There are lots of ways to display search results, and the familiar (if impoverished) ranked list of links with snippets is just one possibility. It doesn’t work particularly well for Twitter, for example because for many kinds of searches it’s hard to make sense of the tweets individually; instead, a more holistic approach is more appropriate. I described in one such approach in Making Sense of Twitter Search (the position paper was co-authored with Miles Efron and was presented at a CHI 2010 workshop on microblogging) .
Paper.li is another approach to visualizing sets of Tweets. For a given topic or user, it identifies documents referred to by your followers and builds a two-column online newspaper-style layout out of those documents. It classifies documents by broad categories (media, education, technology, etc.) and prominent hashtags (e.g., #facebook), show the leading paragraphs or two of the document, and the person who tweeted it. Media such as YouTube videos are embedded directly into the layout. And, you can, of course, switch to a list view.