I’ve been maintaining this blog, or at least the content inside it for about five years now. It’s been through a handful of incarnations, often paired with significant changes in web hosting. I’ve had a blog for a little bit longer, but I don’t think I have the medium figured out. The structure of the posts and the style has changed over the past few years, but I can’t at this point call it evolution, a positive progression. Part of the power which lies in analyzing data is the ability to realize patterns, often at a different scale from human observation (spans of months or years) which are equally if not more insightful.

That’s been my personal attraction to data science. I’ve had a couple of personal experiments involving collecting data about my daily activities, my old writing and code in hopes of distilling the changes that I’m too conceited to admit without the infallible hand of statistics. For nearly two years now, I’ve logged my entire life within precision of approximately 30 minutes from Google Calendar (or the Calendar app on iPad which syncs to Google Calendar). Actually, the label is slightly off, I quite often dedicate large spans of time to more or less useless labels like “not productive”. But this temporal information falls apart in terms of its richness, for my schedule is dictated more so by the mandatory rhythms of school life than the drifting cadence of other behavior.

But I digress. This isn’t about why I collect data so much as “I have this data, now what?”. In this case, I had a hypothesis, a rather simple albeit morbid one at that “my blog is dying”. It’s not hard to see how I’m coming at the conclusion. I’m pretty much struggling at this point to meet my goal of one post per month (itself not a particularly difficult goal, but as time has gone on and my posts have become more infrequent, I feel more compelled to write obscenely long posts to compensate, but of course this also leads to big posts sitting there unfinished for long durations losing the sort of one post = one sitting mentality). But before I ramble for too long, I’ll cut to the chase and answer the question posed at the beginning of this paragraph: “Graphs.” (you could imagine those haunting glyphs levitating in the midst of air caught in the invisible grasp of Giorgio A. Tsoukalos, or better yet, I can spare your cognitive abilities by making it real)

blog-post-frequency

Here’s a pretty little graph I made in R (sorry for the mess on the horizontal axis, and I just realized I have no idea as to how to interpret the dates, I’m assuming that they’re linear and it’s just some odd aliasing issue that makes even-numbered years repeat twice), it’s a histogram of the dates of posts that I’ve made to this blog (extracted with a simple Python script and Wordpress’s built-in Export button).You can probably actually tell that the blog’s demise is quite a long way’s coming. Every annual peak ends up shallower the following year and the first time gaps have actually existed was this fateful year, 2012.

It’s actually sort of interesting that these peaks exist, but I can’t really tell during what months that happened during (since these axes are labeled so terribly, it’d be nice if I knew some nice interactive graph engine that worked with histograms, something like that cool time series viewer that Google had for Finance for like ever but for histograms, but I guess that just shows how much of a non-scientist I am, to have no idea how to fluently articulate in a statistical or graphical language of my choice).

Word Count Plot

For more graph fun, here’s a scatter plot of word lengths as a function of year. I wasn’t dedicated enough to figure out how to get NLTK to tell me the Gunning-Fog, Flesch-Kincaid or ARI value for individual posts, and I doubt that would end up showing anything particularly insightful. But yeah, so here it is. Charts. Charts of words. Note that thing that sticks out clocking in at around 3724 words is my first Music Alpha post.

Actually, I won’t mind that Wordpress isn’t yet self aware (‘ello Skynet) and still sends trackbacks and pings (whatever they are) to me when I link to myself. Seriously, you don’t actually need to have a self-aware artificial intelligence in order to learn how to not spam me with emails when I’m quite probably as in super definitely aware of its existence. But anyway, I guess I’ll stomach the lurching pain of a thousand emails (I’m using hyperbole here, in case your rudimentary artificial intelligence algorithms can’t quite distinguish them, but I’m also pretty sure your algorithms wouldn’t be able to handle n-th degrees of meta, so this excruciatingly useless parenthetical wouldn’t be much other than that: excruciatingly useless) and post the last part of the list here.

1340133957.0 , 2012-06-19 19:25:57 , 1178 [http://antimatter15.com/wp/2012/06/pinball/](http://antimatter15.com/wp/2012/06/pinball/)

1333025085.0 , 2012-03-29 12:44:45 , 1302 [http://antimatter15.com/wp/2012/03/musicalpha-v2-0/](http://antimatter15.com/wp/2012/03/musicalpha-v2-0/)

1293394934.0 , 2010-12-26 20:22:14 , 1409 [http://antimatter15.com/wp/2010/12/drag2up-v2-drag-and-drop-uploading-for-all-sites/](http://antimatter15.com/wp/2010/12/drag2up-v2-drag-and-drop-uploading-for-all-sites/)

1317686582.0 , 2011-10-04 00:03:02 , 1565 [Haven't actually published this yet, hmm]

1341591648.0 , 2012-07-06 16:20:48 , 2117 [http://antimatter15.com/wp/2012/07/cloudfall-a-text-editor/](http://antimatter15.com/wp/2012/07/cloudfall-a-text-editor/)

1307064165.0 , 2011-06-03 01:22:45 , 2180 [http://antimatter15.com/wp/2011/06/why-the-chrome-web-store-is-bad-for-the-web/](http://antimatter15.com/wp/2011/06/why-the-chrome-web-store-is-bad-for-the-web/)

1277922545.0 , 2010-06-30 18:29:05 , 2319 [http://antimatter15.com/wp/2010/06/wave-embed-api/](http://antimatter15.com/wp/2010/06/wave-embed-api/)

1294958307.0 , 2011-01-13 22:38:27 , 2762 [http://antimatter15.com/wp/2011/01/the-ambiguity-of-open-and-vp8-vs-h-264/](http://antimatter15.com/wp/2011/01/the-ambiguity-of-open-and-vp8-vs-h-264/)

1308832860.0 , 2011-06-23 12:41:00 , 2872 [http://antimatter15.com/wp/2011/06/samsung-series-5-chromebook/](http://antimatter15.com/wp/2011/06/samsung-series-5-chromebook/)

1305426252.0 , 2011-05-15 02:24:12 , 3724 [http://antimatter15.com/wp/2011/05/uploading-mp3s-to-google-music-beta-from-linux-chrome-os-win-and-mac/](http://antimatter15.com/wp/2011/05/uploading-mp3s-to-google-music-beta-from-linux-chrome-os-win-and-mac/)

That list was compiled by the command cat blogtimes.csv | sort -t',' -k3n | tail, and that’s quite an accomplishment because I had to look up the arguments for the sort command in order to figure that out. Of course, blogtimes.csv is the output of my magical six line python script (which uses BeautifulSoup to extract all the wp:post_dates).

So, with 10 blog posts in that list, every single 8 of them happened after 2011 and 3 of them happened in 2012. Considering that there were 10 things published in 2012 (according to my dataset) and 21 in 2011, that’s a rather significant fraction of the stuff which has been written recently to be insanely long.

Wordpress tells me this post is now at 948 words, so I guess I’ll add a bit of concluding at the end to push it over the magical power-of-ten barrier, so presumably you should brace for the terrible boom which occurs at this point (oh, what’s that? I think that’s my imaginary telephone operator who informs me when I make a factual error, apparently those kinds of booms only happen with waves, and apparently words flowing through word count orders of magnitude don’t count).

The original title of this post was “Meta Analytics & Upcoming Changes”, but in the spirit of the upcoming changes, I’ve moved the “Upcoming Changes” part into its own post (tentatively titled “Upcoming Changes”). You can probably at this point guess that “Upcoming Changes” involves something to tackle the excessive verbosity and to mitigate the absurdly infrequent posts. This probably doesn’t sound nearly as heroic to you as it does to me, because I’m listening to The Avengers soundtrack right now, and “A Promise” is pretty dramatic.

392722_2010404474880_380090264_n

You might have noticed that I haven’t written much for this blog in the past few months. In truth, it’s because of school work, which has never really been something of an issue before. This is, quite probably the least productive stretch of time in my life thus far. I have a suspicion that this issue stems more psychologically than due to some radical increase in work load, but I haven’t looked in to testing that hypothesis (I’ve been collecting data hour-by-hour about what I’ve been doing in the past two years, so I could probably look into it if I were actually interested in that matter). But school’s nearing a close, and hopefully I can get back to a more productive lifestyle, maintaining my blog and most importantly, trying out cool things. I have a few things which I am working on at the moment which should be completed in the coming weeks (though I make no assurances). But since I have an internal goal for writing one blog post per month, I’m going to recycle a project from December of 2011.

Nearly every day, I inevitably end up glancing at my Facebook “buddy list” of sorts, wondering how many people are online. It’s a figure which almost always seems to depend on the time of day, and behaves almost like clockwork, there’s always a massive swarm of people online around 10-11pm, and hardly anyone is ever online at 4 in the morning. I guess the problem with drawing any conclusions from this in particular is how specific a group this graphic represents. It constitutes my friends, and in particular, my Facebook friends. Essentially all of them are people I’ve encountered in real life, and may or may not actually find interest in. But the thing that unites just about everyone is that they’re generally high school aged.

Before going on discussing how pretty of a chart this is, I think it’s worth going through what this chart actually represents. It’s quite easy to tell that this is in fact a polar chart, and on the inner circle, you can tell that it’s a 24 hour clock. Each of the rings represents a friend, and the rings are sorted by the total amount of time spent on Facebook in the given period. So you can see that toward the middle, the graph is almost opaque at every time, whereas on the fringes, the online activity is quite erratic and infrequent.

So, where does this data come from? It’s actually quite simple to get from the Facebook API. I have a cron job which runs every minute to run a FQL request and save the results to a specific log file.

The actual FQL which runs in order to retrieve the list of online users is

SELECT uid, name, online_presence FROM user WHERE online_presence IN (‘active’, ‘idle’) AND uid IN (SELECT uid2 FROM friend WHERE uid1 = me())

Basically, get the User ID, the name, and their online presence state for friends who are either active or idle in the list of the logged-in user. Since Facebook is an OAuth2-type API, you need an access token in order to do anything cool. I just use the Facebook Graph API Explorer to generate my access tokens. Just go press “Get Access Token”, and select (at minimum) the permissions “user_online_presence”, “friends_online_presence” and “offline_access”. Then copy and paste the revealed token into some authkey.txt and you should be set.

I have a python script to go through the log file and to render it as the polar chart which is depicted on the top of the page. The code used for that is frankly atrocious and the output is even more so. Python Imaging Library is used, which is a lovely library, except not for drawing graphics. There isn’t any smoothing or anti-aliasing on the arcs drawn by PIL and they all look hideous. So I render the chart at some absurdly high resolution and down-resize it in GIMP while adding layering, blurs and opacity in order to make the picture somewhat less atrocious. Also, it does’t support restricting the app to drawing a specific day of the week, even though it might be interesting to see the how the trend differs on a weekday versus weekend.

Something interesting about the appearance of the polar graph is that it almost resembles something of a digital fingerprint, and that brings up some interesting privacy considerations. Inside that graphic are the Facebook browsing habits of some two hundred people. There’s the question of how much this changes day by day for users, and to what extent this can be used to identify people. And even if a single ring doesn’t unambiguously represent a single person, the two hundred or so rings of their friends probably goes pretty far into identifying people. There’s also a striking amount of uniformity that says a lot about the type of people who I tend to associate with. Just at a glance, one can tell that there are very few people I’m friends with on Facebook who live in different timezones. Maybe what’s more dangerous than being able to identify a person is to be able to identify what kind of groups that person belongs to. And over the course of a day, just about everyone checks Facebook a few times.

sin(sqrt(sq(x)+sq(y)))/sqrt(sq(x)+sq(y))

http://antimatter15.com/misc/f(x).html?sin(sqrt(sq(x)+sq(y)))/5.html?sin(sqrt(sq(x)+sq(y)))/5 )

http://antimatter15.com/misc/f(x).html?sin(sqrt(sq(x)+sq(y)))/sqrt(sq(x)+sq(y)).html?sin(sqrt(sq(x)+sq(y)))/sqrt(sq(x)+sq(y)) )

I think function plotters are cool, and since 3d is all the hype nowadays, why not make a 3d function plotter? I like how WolframAlpha does it quite nicely, but it doesn’t allow panning/moving of the camera. Just as a disclaimer, I made this because it’s cool, not because I spent lots of time on it, on the contrary, it’s taken from the three.js 3D Canvas library floor demo with a 3 line change to make it pull a function from the URL.