Things That Make Me Unsubscribe, Unlike, and Unfollow

-Blog guest posts. I have a short list of blogs I read regularly, and I read them regularly because I enjoy the topics AND the unique viewpoint AND the quality of writing. Don't muck around with this perfect storm by allowing other people's writing to come into my feed under your auspices.

-Creeping photoblogging. Similar to above. I myself don't follow any photoblogs, but some people do. However, using a blog platform you created using your writing as a way to make people look at your photos (no matter how good) is self-indulgent. Put 'em in a separate feed, or just link to your Flickr/Instagram/whatever stream.

-Podcasts and videoblogs. They are an insanely slow way of taking in information, and we hates them. If you must publish them, providing a transcript is not optional. (Note: this applies less to entertainment, more to thoughtful content).

-Contests/deals requiring entrants to retweet your message verbatim or use it as their facebook status. I'm not going to subject my friends or followers to your promotional messages just to win a free copy of your book, free concert tix, etc. Better alternative: require contest entrants to @mention you or link to you in their facebook status - at least this way your fans exercise a little individuality in what they say about you.

-Cluttered blog pages. Unlike many other types of websites (entertainment, gaming, etc.), people are at your blog to read (and maybe share or respond). Make achievement of this goal easy by using a clean design, avoiding over-use of logos and graphics,and minimizing the amount of sales-related content you force on them in the sidebars (Amazon store links, etc.).

-Inappropriate usage of location-aware tools. Right (or at least defensible): checking in on Foursquare to see who else is there. Wrong: routing all check-ins to your facebook/twitter profile. Also applies to trip- and event-planning tools (TripIt, Plancast, etc.)

Short list of other, slightly more venial sins: links in blog posts that don't automatically open in a new tab/window. re-tweeting services that drop off or break the links. profile pics and avatars that don't contain, primarily, your face (logos are acceptable for companies, but not photos of your children, pets, etc.). non-ironic use of 'hubby', DH, 'my lady' and similar ways to refer obliquely to your significant other.

Coolest web fact I did not know:

Via Wikipedia:

reCAPTCHA supplies subscribing websites with images of words that optical character recognition software has been unable to read. The subscribing websites (whose purpose is generally unrelated to the book digitization project) present these images for humans to decipher as CAPTCHA words, as part of their normal validation procedures. They then return the results to the reCAPTCHA service, thereby contributing to the digitization project. The result is that the university receives approximately 3,000 man hours per day of free labor to help in the preservation of books.

I always thought those words with squiggly lines were just especially clever CAPTCHA tests; I had no idea they were actually part of an incredibly cool distributed processing scheme. Spammers, of course, have learned how to use a reversed version of this system where a program entices real humans to decipher CAPTCHAs, in return for which they get to view racy images for free.

Checking the mood of the internet.

Via Mind Hacks, I found We Feel Fine, a site that collects feelings (statements from bloggers about how they're feeling) from the internet and catalogues them. I've only fooled around with the interface a little, but there are many options for looking at the data in interesting ways -- by location, weather, gender, age, type of feeling, and so on.

The methodology: The data collection engine searches blogs for sentences containing 'I feel' or 'I am feeling,' locates the full sentence and saves it. Then it checks the sentence for any of its 5,000 'feelings,' adjectives and adverbs entered in by the developers. If there's a match, the engine looks in the blog's profile to find out the location, age, and gender of the 'feeler;' it also uses the location data to look up current weather conditions. According to the site, the engine acquires between 15,000 and 20,000 feelings each day.

These basic, raw feelings create the first view of the data, but there are several others which model various statistics about the feelings. As of now, the mood here in Boulder is pretty good, to which I add the following statement: I feel zestful. I wonder if that's in their 5,000 pre-approved feelings?

The (Web) Search for Spock

An InformationWeek article describes Spock.com (currently in beta testing), which allows users to search for profiles compiled out of public information, vote on how accurate the information is, and manage the accuracy of their own profiles. The site is also running a contest (the 'Spock Challenge') to find solutions to one of its major problems, teaching a search algorithm how to correctly tag new information when people share the same name.

The site is currently by invite only, so while I'm waiting for mine, let me just say this: the creators claim that they named the site Spock for its consumer recognizability factor, and that it stands for Single Point of Contact and Knowledge. To which I say: Yeah, right. As a long-time Star Trek enthusiast, I'm comfortable admitting that I've had a crush on Mr. Spock since high school, and I find it hard to believe that the 'patron saint of computer science' had nothing to do with the naming of the company.

Will report back on Spock's search capabilities soon. In the meantime, here's my favorite sentence in the IW article:

"In the absence of privacy, control is the next best thing, and Spock stands out for giving its users a least a little say over how they and others get represented online."

Italics added -- I'm thinking the company could get this printed on a T-shirt, with an image of Spock looking severe.

Early Friday time suck: do your part to organize the universe.

Following the trend of using human brains to do visual classification work that is easy for us, hard for computers, GalaxyZoo.org uses web surfers to classify the million galaxies being photographed by the Sloan Digital Sky Survey. Procrastinators, follow me!

More on neural networks (and how to win at 20 questions).

As I was thinking about interesting applications for artificial neural networks, I happened upon 20Q.net, a surprisingly addictive ANN-based 20 Questions Game. I tried out the Classic, Music, and Harry Potter games; I was able to stump the Music game about half the time, but only fooled the others very occasionally. This confirms an intuition about neural nets -- they learn best when their universe is small, when they get lots of human input, or both. The classic game is very general, but also almost 20 years old (works well due to plenty of human feedback); the Harry Potter game is relatively new, played frequently, and only deals with objects within the HP universe (works even better, due to the limited universe and the sheer number of HP enthusiasts out there). The music game is fairly new and very general, and doesn't work well at all. It asks silly questions that aren't appropriate based on earlier answers, and fails to ask really obvious ones. You might expect as much from a computer, of course, except that the other two games were a lot like playing 20 Questions with a real person who happens to be way smarter than you. These two skilled games ask questions that are unexpected, but make sense once you ponder them. And they're eerily good at guessing the answers.

So what? Well, this is interesting to me because I've been thinking lately about search engines. The only commercially available search engine I can find using neural net technology is MSN Search, introduced in 2005. It uses a centralized 'supervised learning' approach -- that is, somebody at MSN (probably lots of somebodies) is in charge of telling the engine which search results are the most on-target. Since the 'universe' here is big (the whole internet), it seems like a decentralized input approach would be in order: have users evaluate the search results, which is presumably what Google's doing with its new facial search module (see recent post and comments). As I've mentioned before, this is what Google's good at -- finding ways to make use of the work web users are already doing anyway.

Meanwhile, and probably next for websearch technology, there's semantic websearch: getting a computer to understand what words mean, so that it can find relevant results more creatively. The cheater's solution to this is the Semantic Web approach, tagging everything on the internet to explain what it is and what it's about in a way that makes sense to search algorithms. The real goal, though, is to teach a search algorithm what search terms mean, or at least what they might mean, so that it can find related content that doesn't use the same keywords/tags. Earlier this year Read/WriteWeb asked, 'Is Google a Semantic Search Engine?' and concluded that G. has at least introduced rudimentary semantic analysis in the related searches it suggests at the bottom of the page. This is based on statistical analysis of word context, though, not on true semantic analysis. Enter neural nets, which are the only way (so far) to give a computer the complexity necessary to 'get' language. More on this to come.

Google's next move

Wired commentator Tony Long notes Google's new Street View, an application launched May 29 that shows you street-level images of major US cities (so far: Denver, Las Vegas, Miami, New York, San Francisco). To accomplish this, Google partnered with ImmersiveMedia, a company that specializes in taking high resolution video while driving along streets; the company then tags the video bits with geographical info. (Till now their main clients have been city planners and the department of defense.)

Long's main complaint is that although privacy on public streets isn't legally protected, Street View is nonetheless a major invasion of the anonymity large city dwellers are used to taking for granted. Google's response to this is a form you can submit to have a particular street view removed; criteria include inappropriate content, invasion of privacy, and personal security concerns. What happens when Google receives a request like this one from an Oakland woman who says Street View clearly shows her cat through her apartment window? Well, it's too early to tell, but odds are they'll be pretty responsive, at least to people like this whose very living spaces are being viewed via Google.

But Long is right to worry about people accidentally being surveilled while leaving an adult store -- or, for that matter, while entering the wrong church, grocery store, or political organization. In the past, city-dwellers who wished to avoid disapproval from their family or community could simply drive across town and do their thing, with relatively little danger of being observed by anyone they knew. Technologies like Street View, though not yet all that useful for casual surveillance, are one of the first steps in dismantling that anonymity. Some more food for thought -- Google has quietly introduced facial searching in its Images search; currently the module just tries to identify which images have faces in them, but it would be foolish to assume Google's not working on true facial recognition, and as I've noted before, if anyone could do this effectively it would be Google. Street-level images combined with facial recognition technology? I don't usually get very exercised about surveillance concerns (I subscribe to the Momus theory of modern privacy) but this creeps me out, just a little.

UPDATE: After generating a huge amount of negative publicity, Google no longer requires photo ID and a sworn statement to get images of individuals removed from Street View, per this Wired blog.

Google: Not Big Brother (Yet)

Ars Technica reports that Google has surreptitiously added facial recognition technology to its image search; the function is apparently only available to those who know the secret search parameters. Currently the technology is useful just for finding pictures that have faces in them, not for identifying the faces, though the AT article predicts that it's only a matter of time. Facial recognition technology, of course, is one of those things that sounds really alarming from a privacy standpoint: If citizens are viewed by surveillance cameras 300+ times a day (as the average Brit is), and if these cameras were enabled with true facial recognition technology, well, any libertarian worth her salt can see how this works out. However, facial recognition technology is alot like karaoke - ridiculously easy to do, but very hard to do well. The concept is easy: give the computer a template for facial patterns, and show it lots of pictures until it understands how to find the face. Then, teach it to distinguish different faces using the same procedure. Heck, babies can do this almost from birth, even with other species (interestingly, adults get worse at it as they get older, and are much worse at recognizing faces in other species). But although there are many facial recognition programs around, they don't work very well to begin with, and are notoriously easy to fool with a different haircut, a hat, or a pair of Groucho glasses.

On the other hand, Google has a knack for solving difficult problems using surprisingly simple solutions. G. revolutionized websearch by eschewing complicated natural language processing options designed to understand exactly what the searcher wants, and instead found a fast, easy way to make a reasonable guess. And facial recognition is ultimately a pretty similar sort of problem -- like semantic language processing, it's accomplished by humans using a complex neural network, which is hard to replicate in a computer (so far). Teaching a program to simply make a decent guess might be a much easier, more elegant solution, which is Google's specialty.