DarwinTunes bills itself as a “test tube for cultural evolution.” It’s an online experiment being run by researchers at Imperial College London. We often talk about the evolution of social media or cultural memes – but is that just a metaphor, or is it really evolution?
Last week I was in DC at the HCIR 2009 workshop organized by Bill Kules, Daniel Tunkelang, and Ryen White. This was the third workshop in the series, and by far the biggest and most diverse in terms of attendees. Proceedings are available online. Daniel and Max Wilson have already given pretty good coverage to what happened at the workshop, so I will focus on my impressions, starting with Ben Shneiderman‘s keynote.
Social media: a bigger game-changer than the Gutenberg press? More popular than porn on the Internet?
Socialnomics has collected some very persuasive stats into this beautifully designed dynamic-text video, “Social Media Revolution.” It’s worth watching in HD, full-screen mode (you’ll need to click through to YouTube for that though). Also, some YouTube commenters take issue with a few of the stats – so I wouldn’t necessarily use this for source material. I think it’s true in essence, however.
Yesterday, I attended a talk by Evgeny Morozov about the way that governments (but particularly authoritarian ones) have embraced social media for the purposes of disinformation and control. The typical assumption that the availability of communication technology increases dissenters’ ability to communicate and to organize is rooted in the example of the fax machine and copier that were used in the USSR to distribute Samizdat (self-published) works. The devices are different these days, but the same equation is assumed to hold: connectivity x devices = democracy. Last summer’s post-election riots in Tehran, with the attendant Twitter narration, were taken in the same spirit.
I have a question. It’s a general question, directed at anyone and everyone.
When one is building an Information Retrieval system, one uses target objective function(s) that give an indication of the performance of the system, and designs the system (algorithms, interfaces, etc.) toward those targets. Sometimes, those functions are open and well understood. Other times, those functions are proprietary and hidden.
My question is: Does it do the users of an IR system a service or disservice to hide from them the function that is being optimized? Or is it completely neutral? In other words, does the user have to understand, or at least be given the chance to understand, what it is that the system is trying to do for them in order to get the best value out of that system? Or can a user get results just as good without having to have a clear mental model of what the retrieval engine is trying to do? In short, does it matter if the user does not understand what the system is trying to do for him or her?
Can someone point me to research that may have looked at this question? If one were trying to publish original research on the topic, how would one go about designing an experiment in which both (1) this hypothesis is tested, and (2) done so in a way that generalizes, or at least hints at possible generalization?
Almost 10 years ago, L. Sweeny published an analysis of summary census data that was used to identify 87% of respondents based only on their ZIP code, gender, and date of birth, data that we all think of (and the census treats as) relatively anonymous. At about the same time, I visited a friend at a large consulting firm who demonstrated data mining software that combined data from multiple sources and was able to discover many facts about people, that while not particularly revealing individually, painted a much more complete picture when federated. Now comes the news (thanks Daniel) that a group at MIT was able to make better-than-chance predictions about people’s sexual orientation using Facebook friends as training data. Whereas the census analysis and the data mining tools could be considered academic exercises on datasets to which most people don’t have access, the MIT results have much more immediate and potentially damaging implications.
Recently Google announced a new initiative: The Data Liberation Front:
The Data Liberation Front is an engineering team at Google whose singular goal is to make it easier for users to move their data in and out of Google products. We do this because we believe that you should be able to export any data that you create in (or import into) a product. We help and consult other engineering teams within Google on how to “liberate” their products. This is our mission statement: Users should be able to control the data they store any of Google’s products. Our team’s goal is to make it easier for them to move data in and out.
This is a fantastically worthy goal, and I whole-heartedly applaud it. However, I am beginning to wonder: What data is yours to own, in the first place?
For example, consider web searching. Continue Reading
In “The Library of Babel“, Jorge Luis Borges describes a library “…composed of an indefinite, perhaps an infinite, number of hexagonal galleries… ” lined with shelves of books. Unfortunately, the books are not organized in any predictable manner, causing librarians to travel “… in search of a book, perhaps of the catalogue of catalogues…” The searches, though, are in vain, given the improbability of finding what you seek in an infinite collection.
I get a fair bit of spam. Every day I delete about 400 messages that my spam filter catches; this blog has amassed over 7,000 spam comments in six months or so; and now, Twitter is getting spammy too. I’ve noticed a rash of twitter-spam-bot followers recently, and am quite confused as to what they are trying to achieve.
I’ve been using SciRate for 2 1/2 years. I began using it with certain expectations, but my actual use has differed from those expectations.
The simplest and most used feature of SciRate is its “Scites” button. With one click, SciRate members can vote for a paper. Initially I wasn’t sure how I should use this feature. What did my vote mean? Should I only vote for a paper I had read? Did it mean I could vouch for its correctness? Eventually my selfishness kicked in. SciRate made it easy for me to see what papers I had scited. And sciting a paper was so light-weight that it became the easiest way for me to mark papers that I wanted to come back to later. I don’t always come back to those papers, but I frequently use my list on SciRate to find a paper whose abstract I vaguely remember reading, or to find a set of papers it would be fun to read over the weekend.