On Friday Netflix canceled the sequel to its Netflix prize due to privacy concerns. The announcement of the cancellation has had a mixed reception from both researchers and the public. Narayanan and Shmatikov, the researchers who exposed the privacy issues in the original Netflix prize competition data, write “Today is a sad day. It is also a day of hope.”

The Netflix prize data example is probably the third most famous example of de-anonymization of data that was released with the explicit claim that the data had been anonymized. These examples differ from the privacy breaches discussed by Maribeth Back in her post on ChatRoulette or the issues with Google Buzz discussed as part of Gene Golovchinsky’s post “What’s private on the Web?” . Those examples made sensitive information available directly. In the case of the following three de-anonymization attacks, the data itself was “anonymized,” but researchers were able, with the addition of  publicly available auxiliary information, de-anonymize much of the data.

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Jeremy scooped me in his recent post where he commented on a recent SXSW panel on social search that included Marc Vermut, Brynn Evans, Max Ventilla, Ash Rust, and Scott Prindle. Jeremy pointed out that in addition to asking for help and embarking on a solitary search, was the possibility (discussed many times on this blog) of embarking on (an exploratory) search together. Searching together, collaboratively, is often appropriate when faced with exploratory (rather than known-item, factiod, or trending topic) information needs. Collaboration works best when information needs are shared, and when the results need to be created rather than merely re-discovered.

In an exchange on Twitter, Brynn pointed out that instances of true collaborative search comprised less than 10% of the instances she and colleagues had recorded in their study of Mechanical Turk respondents. But that argument misses the point.

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(Please be aware that some ChatRoulette links may contain mature content.)

Dear me. All those folks doing naughty things on ChatRoulette, secure in their Net-anonymity, may suddenly meet a rude awakening: Chat Roulette Map, a new Google Maps mash-up, maps users’ chat image to their location, based on IP address. Last week, it also showed users’ ip addresses.

Note that Chat Roulette Map has just added a new pop-up window when you first load the page:

Welcome To Chat Roulette Map
(snip)
We’d like to advise maine.edu to stop using
student’s names in their hostnames.

We’ve decided, at least for the time being, to
hide IP & host information as some user-identifiable
information was found in some entries.

No, you think? It’ll be interesting to see how this warning window evolves over the next few weeks.

Instead of talking about lofty research ideas today, how about something more prosaic that lots of us do behind the scenes here — programming. Specifically, a topic I’ve wrestled with recently in my first big project using WPF: How do you productively use object inheritance in your custom user controls?

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Our friend Takashi Matsumoto, (who built the Post-Bit system with us here at FXPAL) built a cubic display called Z-agon with colleagues at the Keio Media Design Laboratory. Takashi points us at this video of a very nicely realized cubic display (well, five-sided, but still). It’s called pCubee: a Perspective-Corrected Handheld Cubic Display and it comes from the Human Communications Technology Lab at the University of British Columbia. Some of you may have seen a version of this demoed at ACM Multimedia 2009; it will also be at CHI 2010. Longer and more detailed video is here.

For the language geeks out there, this month’s SDForum Emerging Technology SIG looks interesting.

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:

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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.

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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.

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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.

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