There are countless videos on Youtube of people trying these things out – stacking barrels in Farcry or balancing helicopters on top of other helicopters in Battlefield: Vietnam.  Constance Steinkuehler, an academic in the field of Educational Communications & Technology, asserts that kids in Lineage and World of Warcraft have been unwittingly conducting experiments according to the scientific method in order to understand the world around them!  This behaviour seems to be quite common.  If you look through any forum dedicated to a game you’ll find extensive write-ups of all the units, power-ups and a weigh-in on whether something is worth having or doing.  Http://strategy.diii.net, a site for Diablo II, h0as links to strategy guides which outline the principles of experiment design. A site dedicated to World of Warcraft,  thottbot.com, calculates the probability of a monster dropping an item to three significant figures!

In one respect, this is a wonderful development.  People are using rigorous, principled methods of investigation in order to understand the worlds they find themselves in.  On the other hand, those environments are not only artificial – video games are necessarily artificial – but worlds with such a feeble resemblance to reality that no relevant knowledge can be gleaned through experimentation.  This is tragic.

This is not an attack on all games, though.  This frustration is aimed at worlds that purport to some degree of realism – racing games where an autopilot takes control when you spin out (Ridge Racer), or momentum values that are tweaked with no justification to make a spacecraft more maneuverable as a game progresses. I don’t think all games have to have Newton-perfect calculations of mass and velocity, but I think there ought to be games that at least try.

Towards that end, here’s another update of what I’ve been working on.  It’s really hard to resist holding off on an update because I’m so close to a breakthrough, but I’ve found that after one breakthrough is made, it always seems ‘close enough’ to the next to hold off again. Consequently, there’s a lot in now that wasn’t in the last build. The list of what’s new is probably less interesting than the thing itself, so here it is:

• Colour sliders: Now, rather than relying on the colour of a mirror being made on the fly, you can select the colour of all the elements, setting a laser to beam only red light, or a mirror to reflect only yellow light etc.
• Rotation: Works now.  You click to select a pivot to rotate the selection about, and drag around to place ‘em.
• Tooltips: Finally, there is a little feedback about what things are and what to do with them!
• Cirlces: Only work with lasers at the moment, but they are solid, circular mirrors that could be considered to have a “mass”.  One day.
• Polygons: These do work with beams and lasers, but do some silly things with beams (when you point the beam on to an angle less than 180º) . These could also be considered to have mass one day.

What’s next?  Remote loading and saving (I’m going to need some help with PHP for that), and then Box2D!  I’ve been messing around with some ideas for games that could actually use this engine, and I’ve come up with one idea, which I’ve sketched out on my Flickr page, but that’s as far as it goes right now.  When I have more, I will show it!

The first two accusations are reasonable – there are a lot of stupid comments out there, and they are very repetitive.  They are so hated by some that someone has developed a Firefox Add-on that will strip comments out of the page before you can even be offended by them.  On the other hand, though, people are very stupid and repetitive.  There’s often a surprising honesty to the statements that people make on youtube. It is suggested that the monumental scale of the youtube ‘community’ means that individuals are effectively anonymous, which liberates users from any self-censorship that would occur from fear of shame or other punishment.  It’s not all honesty, since people are more likely to be offensive if they know they can get away with it, but it’s a refreshingly different place to look for views and opinions in.

So while they may be stupid, they’re still worth looking at.  The issue of quantity is more of a practical issue, though.  For example, I keep tabs on  a video called “The Most Pathetic Baby Panda Ever”. It has almost 5 million views and 15,500 comments.   Even if you only dedicated 5 seconds to each comment, you have to spend over 21 hours studying them. The Evolution Of Dance has almost 250,000 comments -   almost two weeks’ worth of study.  While they’re interesting, they’re not that interesting.

Conveniently, though, this is exactly the kind of thing that the study of data mining is supposed to deal with.  In addition, the fact that the comments appear to be stupid (or simple,) and highly repetitive works in our favour. The first question I would try to ask of these comments is “what’s a typical comment?”  and toward that end, I have created the Youtuber.

There are at least 80 million videos on Youtube [wikipedia], and if the average length is at least one minute, then it would take about 160 years to watch them all (with no waiting for loading).

There are at least 1.5 million CCTV cameras deployed in public places in the Greater London area [also wikipedia], meaning that if a person could watch 16 cameras at once to monitor them, you’d still need almost 100,000 people, or around one out of seventy living in London employed to watch over the other 69. (If we broke it into reasonable chunks, you’d want 4 full-time shifts of people, pulling the number up to 400k and the ratio down to about 1:18!

Project Gutenberg, wonderfully, has over 100,000 books on offer for download. If we assume that the average book is 100,000 words (a novel is generally supposed to be about 230,000 or so; the English translation of Les Miserables is 650,000) then it would take 90 years (of constant reading at a pace of 240wpm) to get through it all.

There are probably hundreds (or thousands, or millions) more examples of where the quantity of information we have at our disposal is so far beyond our perceivable reach that it becomes effectively unusable. This is why we need to find a better way to work with large quantities of information – a way of “Data Mining”, if you will pardon the phrase.

It’s true, datamining is becoming big business, and all of the big IT companies are doing it – but when was the last time that you did it? Unless you work at one of those big IT companies, probably never.

That’s something I want to change.  One of the programs I’ve been making recently, the Youtuber, lets individuals do some basic analysis on one of the most frivolous data sources out there – Youtube comments.  It is my hope if we make better tools for data analysis for the everyday user, they will learn something new and interesting about the world.

Not to mention what we might find when we turn this analysis back on ourselves! But that’s another story.

I was trying to make a function that would be able to indicate the correlation of two keywords to one another over the volume of youtube comment posts.  That is, if 50% of comments contained the word “awesome” and 50% of the comments contained the word “lol”, then it would be expected for about 25% of the posts to contain both.  I decided that green should indicate “about expected” correlation, cyan “above average”, blue “very high”. On the other side, I would choose yellow for “below average”, and red for “very low.” 

Messing about in paint, I figured out where I wanted my red, green and blue values to move in and out, and once I had those states working I would interpolate between them.

just another gradient

The colours didn’t work out properly at first, but it I like the gradient here anyway. It’s interesting when the mistakes look as nice as the successes.

This is the state of the links in the youtuber as of today. the colours here are for values between 0.25 and 6… because the function is piecewise, nothing interesting happens past 2.0… it was gratifying to get it working though.