A panel of experts faces off over the relative strengths and weaknesses of three emerging languages – Clojure, Scala, and Go - and one “benchmark” language - Ruby. Details:
We have a continuing interest in alternative energy sources and other green technologies. I’m intrigued by this article at phys.org on new solar-based fuel cell technology coming out from MIT chemist Dan Nocera. Why it’s cool:
With one bottle of drinking water and four hours of sunlight, MIT chemist Dan Nocera claims that he can produce 30 KWh of electricity, which is enough to power an entire household in the developing world. With about three gallons of river water, he could satisfy the daily energy needs of a large American home. The key to these claims is a new, affordable catalyst that uses solar electricity to split water and generate hydrogen.
Nocera’s new company, Cambridge-based Sun Catalytix, recently received funding through the new ARPA-E agency that was created by the US government to promote the development of advanced energy technologies. Take a look:
Michael Bernstein and the usual suspects wrote a nice position paper for the CHI2010 microblogging workshop. They describe Eddi, a system that allows people to group tweets by topic to make sense of large numbers of tweets. In some sense, they are addressing a similar problem to the one that Miles Efron and I tackled in our paper. In both cases, the system uses various sorts of analysis to group and filter tweets to help people understand the collection or the stream.
Kate Ehrlich and N. Sadat Shami have written a paper (accepted to ICWSM 2010) that compares IBMers’ use of Twitter and an internal micro-blogging tool (with the unfortunate title of BlueTwit). The paper analyzes tweeting patterns of 34 people over a four month period. The authors found that people in their sample tended to use both system more for question asking/answering and dissemination of information than for status updates, which contrasts with Namaan et al.’s finding that “meformers” (i.e., people who tweet about what they are up to) out-number “informers” in the sample they analyzed.
Ehrlich and Shami’s study found that people used these tools to improve the social status: internally to manage their reputation, to be seen as a source of useful answers rather than just of questions, and on Twitter both to promote their company and to develop their professional status.
I’ve been using TweetDeck for over a year now, both on my laptop and on my iPhone. It’s a great tool for managing a moderate stream of tweets. The columns offer a convenient way to segment and organize tweets, and its display of certain media in-line is convenient. In the spirit of constructive criticism, I would like to offer a set of suggestions (some obvious, some maybe not) on how its user experience might be improved.
Marti Hearst gave an interesting talk at JHU on Social Media in which she described some important dimensions of through which we can understand the variety of phenomena that are tagged with that label. She examined expertise, the degree to which data are shared (synchronized!) among the people engaged in some activity, and the degree to which participants are working toward an explicitly-shared goal (even if they approach it different personal motivation).
Apple.com has a lovely article here on the iPhone app we built so our collaborators at TCHO could monitor and control their chocolate lab machines remotely. This work is part of our explorations in mixed reality for industrial enterprises, in particular the Virtual Factory project. Below you can see a few screenshots from the iPhone lab app (click for larger image).
Daniel Tunkelang wrote about Herb Simon’s attention economy and ways to measure the way people allocate attention. His example of attention-switching and interruptions with e-mail made me think about individual differences. People differ in the willingness to engage in an activity, and self-interruption is a common practice. You can measure time on task, but for complex cognitive tasks it is not clear that time is a good predictor of performance. The problem of measurement is more complex than simply aggregating times or counting switches.
In HCI, we have a notion of the fallacy of the average user — the notion that if you design for characteristics averaged over a large number of people, there may not exist a single person for whom the design is ideal. This due to the fact that certain phenomena have bimodal distributions rather than those with a central tendency. For example, Hudson et al. found that individual preferences in interruptibility suggested a bimodal distribution.
Social computing is the future of interaction, explains Michael Bernstein, and he has a point. Leveraging the work of others rather than recreating it is the way civilizations are built. But that is not the whole story. There are instances when leveraging the work of others is the right thing to do, but there are also many situations where it is undesirable for moral, aesthetic, and practical reasons. The moral side is obvious — the undesirability of appropriating others’ work without their permission isn’t that controversial — but the aesthetic and practical aspects of reusing others’ content bear some additional scrutiny.
