Michigan Library Web 2.0-ed; Husband 202-ed

As if we needed further proof that taking 202 can change your life (or your wife), my husband today sent me an email worthy of mentioning on this blog. I think he has been vicariously 202-ed. What he felt compelled to share with me was the fact that the University of Michigan Library has a feature on its Mirlyn search engine where users can tag any item in the collection. I checked the UC “next-generation pilot” version of Melvyl, and indeed it supports tags as well, along with social bookmarking features. It’ll be interesting to see just how Weinbergian our libraries get in the next few years. I think this is a good thing, because it shows that libraries are paying attention to what is going on outside and are not afraid to experiment with it. Long live libraries!

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The Silicon Tower

BBC News’s Aleks Krotoski has a thought-provoking op-ed piece about how technophilically skewed the bulk of the internet really is. Her observation is based on spending some time with people who simply don’t use the web. She points out that they are not luddites but people who have simply found that the web doesn’t speak their language, doesn’t share their ways of structuring information. She mentions issues with search facilities like Google, but she also points out that even approaches meant to be more democratic (e.g., the semantic web, or facilities based on the intelligence of the masses) fall short for people who are not technologically oriented because the creators of web sites and the presumed intelligent masses are dominated by technophiles. For us 202ers, of course, the differences in how people organize information are nothing new, but it’s good to remind ourselves now and then that, as aware of the differences as we are, we are ourselves members of a particular community of thought. We at the iSchool are, I think, too focused on serving the needs of society to be considered residents of the traditional ivory tower; we live instead in a silicon one.

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Minnesota Public Radio does broadcast information right

After looking at the YES API in class on Monday and hearing everyone’s complaints that it couldn’t possibly be right, I wanted to share an example of great radio broadcast listings. Minnesota Public Radio has complete listings of music played on both their Classical and Current (modern) stations. The default view is all music played on the current day, broken up by hour, with links to purchase the albums. In addition, you can search for songs played as long ago as 2005 or 2006, in case you want to find something you heard a while ago.

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games with a purpose – computers can guess your gender

I am sure, that mostly everybody has already heard of the work by Prof. Luis von Ahn at CMU. His game ESP (for extra sensory perception) had been widely covered by all kinds of media. The game was licensed by Google to create (the not as good) Google Image Labeler. 

Luis von Ahn was already quite famous for his work with stenography, when he came up with Captcha’s to help solve the spam problem. And if that was not enough – he has been coming up with amazing games that help computers become more smart than ever. 

We play, to help computers learn. I like the idea. Check out some games at GWAP.com

Interesting article on Luis von Ahn by Wired

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“Genius” Feature Makes Music Miscellaneous

As many of you probably already know, last week Apple released iTunes 8. One of the most interesting features announced in this update is Genius playlist creation.  Select any song in your library and the Genius will create a playlist of songs in your own library that go well with it. So, if you’re in the mood for jazz, just select your favorite Ella Fitzgerald song, press the genius button and you’ll have a playlist of songs like it.

In my use of this feature, I’d say it works really well. It saves a lot of time and reintroduces me to music I already have but may not have listened to in a while).

Where this feature gets interesting is in how it relates to the material we’ve discussed in 202. The Genius works by first collecting and submitting (anonymously) all of your music’s metadata to Apple’s servers. There, these data are analyzed and compared to other users’ music metadata as well as the buying habits of iTunes music store customers, of which there are about 70 million. The algorithm that Apple uses to determine music matches has in effect made music miscellaneous. People buy music from the iTunes store, rip CDs, and tag their own music files anyway. This feature taps into these disparate cataloging systems collected from millions of users and creates something new from them. It ameliorates the problem of having to recall all the music you have your library that might fit a particular mood. No music professionals required. 

To me, this is a clear win for Weinberger.

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The core metaphors of words…

As we learn about the traditional categorization systems of IO (Svenonious, Lakoff, etc) and contrast them with the tools of next generation systems like XML and tagging, my thoughts continue to hover about a personal interest of mine which is the “ethics” of journalism and (failed?) attempts at both political and journalistic neutrality. In relation to IO, I am curious if established social definitions of terms, phrases, and colloquialisms (ex. lip product on a farm animal) can be used to deconstruct what is “meant” by an author, news feed, source, interviewee, speaker, etc.

Might a database that tracked the core metaphors implied by words and phrases somehow serve as a dissecting blade or is it up to an active community to closely watch the feeds and tag at will? Can an algorithm parse the subscripts of language? In light of our reading on machine translation, tracking bias seems like an even more distant and difficult goal.

So, two interesting tools showed up in my feedreeder this week and I thought it would be interesting to hear any opinions you all might have.

1) SpinSpotter – a Firefox plug-in that…uses “professionals” to build a set of rules, an algorithm to parse articles against said rules, and a community feedback model to track and tag.

Here is a BusinessWeek article about it.

I’ve installed it, but found that since it is in Beta, there doesn’t seem to be much feedback in the system yet.

2) And… Cognition, a Natural language processing database by Cognition Technologies. They claim that it is the “the largest commercially available Semantic Map of the English language.” RWW Article

They state that their system “Understands the meaning within the context of the text it is processing”, which seems promising. If a series of “loaded” words appears in a phrase, is that a sufficient index to call an author biased?

Anyway, if anyone has an interest in this area of information work, I would certainly like to talk more about it.

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