I’m publishing a new kind of puzzle called a Kennie. It’s similar to a KenKen, but has a few minor differences. Kinda like those chocolaty sandwich cookies that aren’t exactly like an Oreo… Kennie puzzles don’t include those cheap freebie squares that make the puzzle easier to get started. Personally I prefer ‘em that way, since it makes the puzzle more satisfying to solve. Your opinion may differ.

Unlike the Times, I’m not stingy: Here are literally thousands of Kennie puzzles, for you to print and enjoy.

Happy solving!

I’m currently working on a significant update to my classic Colr Pickr. Stay tuned.

You can download the resulting list, which contains over a million words, here. Each line shows how many books each word appears in. A second list, which shows how many times each word occurs in total, can be downloaded here.

I prefer the list that shows the number of books each word appears in. It has the effect of pushing down words which appear a lot in only a small number of books, such as the names of fictional characters.

I compiled these lists because I wanted to make some word puzzles. There are lot of free lexicons, or word lists out there, such as the ENABLE lexicon which is commonly used for scrabble-like games. However, for the purposes of making crosswords, word searches, and other puzzles, it’s very helpful to restrict the words to more commonly used ones, and to know how common each word is.

The popularity number of the word correlates well with how ‘juicy’ the word is, or appropriate for a word puzzle. For example, using my book count list, words at the very top of the list are quite boring structure words.

18374 by
18054 and
18023 the
17994 of
17963 a
17955 to
17946 in
17916 from
17912 with
17909 for

As we head towards 10,000, we encounter most of the common bread and butter words. These are also kind of boring.

15095 case
15094 none
15091 taking
15070 seem
15060 able

10776 buried
10771 report
10767 asking
10767 clean
10764 occurred

As we head from 10,000 to 200, the words get increasingly more interesting.

9781 plainly
9781 flat
9779 proofreading
9777 passion
9775 approaching
.
.
.
5999 commanding
5998 channel
5997 translated
5996 metal
5996 sixth
.
.
.
1999 conflicts
1999 spider
1999 bleed
1999 discrimination
1998 lends
.
.
.
599 studs
599 niggardly
599 symbolized
599 engraven
599 palliate

There is a sweet spot with a lot of very juicy, but still familiar words in the 300s. If I were selecting words for puzzle construction, this is the area I would favor. After the 300s, the words start to get increasingly more obscure.

359 pajamas
359 dressings
359 thievish
359 anatomist
359 ticks
.
.
.
200 darkish
200 acclimated
200 unfriendliness
200 moveth
200 undiscoverable

At the 200 mark, we’ve only covered about 38,000 words. There are 1,236,759 words in the list total, so we are are still at the top of a very long tail! Below 200, words get increasingly obscure, archaic, misspelled and foreign. We also hit a lot of proper nouns. Still there are a few legit, but rarely used words mixed in.

99 tingeing
99 marshmallows
99 somethings
99 feelest
99 petrify
.
.
.
50 anim
50 makeweight
50 godard
50 seraglios
50 vun
.
.
.
25 admiralties
25 vanni
25 senescent
25 futrelle
25 erechtheum
.
.
.
10 foretime
10 chargee
10 cabinetmaking
10 pneumonias
10 olivo
.
.
.
5 guisers
5 hairing
5 hipless
5 turms
5 arpasia
.
.
.
1 raskolink
1 baetan
1 succories
1 denudement
1 trotudas

UPDATE, March 23rd:

I measured the average book-count of the words in all the New York Times crossword puzzles since 1997 (their online archive goes back to about 1996). For each puzzle, I averaged the book-counts of the words that appear in my list (typically, about 80%-90% of the words in each puzzle). For most years, the average book-count falls between 2,008 and 2,180, and from year to year, the results can be surprisingly consistent.

Here are my averages:

1997 2070.93
1998 2154.20
1999 2113.24
2000 2180.20
2001 2131.94
2002 2141.65
2003 2115.29
2004 2114.60
2005 2034.01
2006 2026.20
2007 2035.31
2008 2033.90
2009 2008.76

There appears to be a marked shift towards more obscure words from 2004 – 2005.

Interestingly, there are only about a thousand words that fall in that NYT-Crossword sweet spot. Here they are:

pondering squarely pregnant paws scold cordiality cooler venturing variance hypothesis forefinger economic untimely dubious shepherds secular minimum pallor degrading fastidious desertion foretold heath discourage wintry wrenched peas raiment pensive reproof ankle flattened moore fisherman peninsula beholding identification wheeling maine unhappiness richmond frantically enhanced gorge extremities joyously stronghold hissed nut bowels repressed lending feasts cavern unfold memoirs onto invade ark structures forbids liver correctness abashed stumble clerical orchestra terrifying enchantment incomparable collapsed paler ballad recalls slack restraining motley rippling circled ardor lambs flapping shrug prettily avarice aforesaid educate glorified acquiescence acquitted dungeon blasted objective persuading fray forts statistics gathers levelled moderately splashed mirrors infected vacancy furs mates grating precipitate confiding ton grazing dispositions partnership momentarily framework attorney regulating fathom nimble ravages surpassing quieted hitting sustaining practiced darkening walled withdrawal unawares exceptionally howard fiend queens horseman dictates quarry waged coral pleasanter badge assurances subsistence italians manned alphabet bower reposed preachers variously anticipating arabian melodious slate hourly bled dejected dreamt discordant stormed purchasing sap unreal parlour dam couples humblest postpone butterflies chaps yells paw freeze forfeit eclipse advertisements dozens quitting romances uphold drunkenness agonies guinea forge tearful twig dispatched windy tidy bitterest dogged wastes disconcerted irritable tunnel contentedly backing uniforms gunpowder mineral pigeons repel pail territories ransom stab draped redemption individually medicines azure bony scissors ma invariable supplement repulsed entreaty capitals forbearance adviser unavoidable raining enlighten holiness countenances untold coil mutilated dancers thankfulness buzzing armor spoiling narrower adhere ardently undergoing indomitable devoting friction thrive ravine diverse floats hazy twain aspire visage quarrelling womanly shields initiative disappointments elaborately civility disobedience splashing festivities disasters bustling vicissitudes monopoly helen raid marshes fitful consigned illustrates apprehensive conscientiously fabulous colleagues profited wharf grievances countryman laurels diversity monastery target pounded conspicuously myriads hostilities atrocious vase overturned redoubled mountainous swallowing layer adherents sparing parchment trampling imaginations laughingly fictitious jet widows picnic prospective valour absorb yankee chocolate courtiers canoe chasm biscuit stairway jars adjustment ancestral roving catholics psychological milder adapt woollen loathsome rowing barracks signing banker grunted slumbers garret midsummer ignoble savings substantially resuming fostered mane prophesied forfeited swan loosed fortifications gloriously vouchsafed oratory jovial crescent stinging stamps commissions lanterns caresses merest universities insurance draughts surmise rebuked valid barbarians revolted humbled emerald contradicted halfway marvels excel nervousness pier stall illustrating grades surly utensils chagrin colouring murders northwest widening pitiable keener kent devilish conventions carving studded mat dwarf weights youngster compels resounded dispatch fried completeness dismissal undecided aiding dimmed plied illumined extensively needing graphic embroidery glimmering sash sauntered sniffed grasses pitcher rapt unerring offences exiled sucked raced fig streaks halo religions rhetoric advising fraught canadian hampered riders profile incur excellency benediction gregory particles diminutive chemistry infants lounging knocks elated mien propped reverent antagonism wade exhaust unduly needy girlish hoarsely mortified hercules initials scar flowery reproduction absorption excelled stains facilitate modify slap grounded wig lavished magnified agility hugh sponge irishman cultivating stalked fumes metals arena augmented enjoined fibre flushing biscuits attends nick soaring follower boom surest rhine proclaiming snatching paramount alluring clambered loom poultry intoxication slaughtered perplexing impaired sleek patting conceited squirrel inventor notably swells ripened click ethics fairies adventurer summoning vocal jove scolded dwellers uniformity sarah prairie capacities unfriendly uttermost hens gear penance unbearable sewed legion disposing mistook prestige organic unparalleled invaders laboriously trench steeped distraction dipping groped slackened beak salutary summits intrusted inanimate flowering reiterated receding jagged adversity safeguard unacquainted stalks axes alps hip mortality perverse apathy weighs julius witnessing epithet childlike lunatic pretends convict oblivious restlessly yarn offense chests runaway dilapidated unfailing verdure cloudless ferry vista toll prettier unearthly enlist feudal penitent scarf encamped dedication mahogany relinquish residents salmon payments meditations tragedies sufferers concludes arnold smoky altars squadron pursuers sagacious abnormal bernard reeled strangled cherry planets combatants bunches feathered fearlessly therefrom canst precipitated likelihood potato conquests intensified columbus hairy slapped scrupulously immemorial buoyant graver warranted senator excesses invading complimentary turks highness factors vindictive shovel tenderest uncanny augustus propositions detection efficacy artful iniquity emancipation listless indolence lease purified grease unoccupied encounters treasurer hereby narrated revel impetus legislative wailed mexican disappoint impertinence abstraction pulls submissive surged falsely sheriff wilder underwent submitting prisons implicitly treasured sculpture spheres trailed impassioned exacted converts pepper coloring noiseless conflagration relatively maddened precincts versed quartered culprit tunes torments birch fairness unsteady terminate offender citadel ado compiled

I’ve been blatantly cheating at foursquare for the past week. I didn’t mean to start the week this way. Most of my friends know me as a responsible father who occasionally plays piano at local open mics, and makes puzzles.

Last Sunday, while checking into the Hill Street Cafe in Burbank using the foursquare iPhone app, I idly wondered, “Can I become the mayor of the North Pole?” So I tried checking into a nearby 7-Eleven. It worked. I tried the Griffith Observatory about 5 miles away. It worked. I tried Disneyland, which is about an hour away. It didn’t work, but I now had an afternoon hacking project.

When I got home, I looked to see if foursquare had an api. They did. So I found a venue that was close to the North Pole, the “Top of the World” hotel in Barrow Alaska, and checked myself into it.

This can be done on the command line using the curl program, like so:

curl -u EMAIL:PASSWORD -d “vid=993842″ http://api.foursquare.com/v1/checkin

Try it! You’ll need to substitute in your own email and password. 993842 is the venue id of the “Top of the World” hotel, as can be seen in the URL of this page:

http://foursquare.com/venue/993842

This venue wasn’t actually in foursquare’s database, so I added it, using the ‘addvenue’ call. I also added a venue for the actual North Pole. It turns out it’s much easier to become the mayor of something if nobody else has ever checked into it.

[ Edit: Some folks have rightly pointed out that you can easily do the same thing with the mobile website (mobile.foursquare.com). For my purposes, as you'll see in a moment, the API was more efficient... ]

Here’s the North Pole venue I made:

http://foursquare.com/venue/995274

Ultimately, I ended up adding a lot of venues. I used Google Earth to create KML files of interesting venues, and wrote a script to import them all into foursquare. I did the same thing with Yelp. I found that foursquare would rate-limit me if I added them too quickly, so I added them two and a half minutes apart. Later, I found that by rotating among multiple accounts while adding venues, I could add them much more quickly.

At some point last week, I devolved into a 12 year old hacker, and I spent many spare hours (and my computer’s spare cycles) abusing the system with a set of scripts operating fake accounts. Not only did I add new venues like the North Pole, but I started persistently checking into coveted landmarks, like the Statue of Liberty.

What can I say? It was fun, and foursquare’s incentives (badges and mayorships) spurred me on. Incentives invite abuse, even from mild-mannered folks like me.

Eventually I amassed a huge number of mayorships, spread among multiple accounts, including the Statue of Liberty, Mount Rushmore, the Lincoln Memorial, Stonehenge and the Taj Mahal, as can be seen in this screen snapshot.

I wrote a script that would walk through a list of venue ids, and check into them one by one. Then I created about 10 fake foursquare accounts, and had them take over different territories.

I created five “Java Monkeys” which grabbed about 120 different Starbucks in different regions (east, west, midwest, south, intl). I identified and targeted hotly contested Starbucks by searching Twitter for recent oustings. My script automatically visited those ones, to the consternation of the new mayors.

I created a fake Martha Stewart who checks into dollar stores and pawnshops when not visiting Martha Stewart Omnimedia and the set of her TV Show.

I created a fake Simon Cowell who visits massage parlors and gets lunch at Hotdog on a Stick when not visiting the Kodak theater.

I created a fake Tommy Chong who is mayor of 130 cannabis clinics.

I created a fake Sammy Davis Jr who checks into casinos and bars in Las Vegas.

I created a “random nerd” who checked into a number of large campuses in the Silicon Valley.

The “Java Monkeys” got the biggest reactions. Foursquare users get far more irate when they lose mayorship of a Starbucks, as compared to a Statue of Liberty or Mount Rushmore. People are much more attached to the small places they visit over and over, and have some personal investment in. The smaller the venue, the bigger the value.

I started collecting badges as well, by checking into places that have tags like “karaoke”, “photo booth”, “gym” and so on.

I was able to get a swarm badge by monitoring Twitter for when a particular location got up to 40 check-ins (this happens at a couple of Tokyo train stations quite regularly) and then checking-in all my accounts at once to trigger a swarm (which occurs at 50 check-ins). This RSS feed is useful for detecting impending swarms.

Finally, I started giving people free sailboats. I found that if you checked into a venue tagged “boat,” you automatically get the awesome “I’m on a boat” badge; and unlike the other badges, it only requires a single check-in. So I started identifying high-traffic places via the above Twitter search, and then adding the tag “boat”. Suddenly, visitors to metropolitan airports and various sports arenas got free sailboats for Valentine’s Day.

My juvenile crime spree is now over, and I’ve “laundered” my foursquare account, by transferring the credentials to a new one. This URL used to go to the account that stole the Statue of Liberty, but now it goes to a new account, because foursquare allows you to reassign twitter accounts, and constructs the URL using your active twitter account.

This is my original account, which is now inactive.

It seems clear that foursquare is going to have some massive authentication issues to deal with if they are going to grow larger than their current size. Some things to consider:

1) Provide additional measures to detect that people actually are where they say they are. I imagine this is not an easy problem to solve: if I send you a set of coordinates, it doesn’t mean I’m actually there. At a minimum, they can measure the time of travel between successive check-ins by comparing the coordinates and time stamps. If I’m traveling close to the speed of sound, something is clearly up.

2) Make it less easy to create fake accounts. Right now, there’s not even a Captcha.

3) Don’t construct a permanent-looking URL from a twitter account (which can be transferred to a different foursquare account). This provides a method of “laundering” accounts.

More generally, I think the combination of a poorly moderated and insecure folksonomy with incentives (e.g. badges, mayorships, free meals, etc.) is a fragile one. The greater the incentives, the greater the motivation for cheating.

As it stands right now, foursquare has quite a few holes. If I were a restaurateur or coffee shop owner, I would be very wary of giving free meals or lattes to foursquare mayors, unless the employees know the mayor by sight.

UPDATE

My story seems to be getting some picked up in a few places. Here’s some reaction on Twitter. Mostly positive, I think, although a few foursquare insiders were a bit put out, as one would expect. Dennis Crowley was quite nice about it, thank god.

If I stole your Starbucks, I’m really sorry about it, and I will gladly buy you a latte, if you find me in a Starbucks.

UPDATE #2: My story was covered on TechCrunch this morning. MG Siegler was mostly on-the-money, except for this bit:

The problem, with regard to false check-ins, is that the only solid way to do this is to a check-in to your actual GPS coordinates. The problem with this, as Gowalla knows all-too-well, is that it can be hard (and in some cases impossible) to get GPS data while users are indoors.

Um, not exactly. The problem is that you can’t trust the person who’s sending GPS coordinates to send the correct ones. This is a tough, tough problem, and it will become increasingly obvious as incentives increase.

UPDATE #3: Foursquare founder Dennis Crowley has provided some thoughtful commentary in the comments, below.

UPDATE #4: The LA Times interviewed me and got a few more details…

UPDATE #5: Alison Cummings of the Montreal Social Media Examiner posted this reaction to the whole brouhaha. I’m going to call her “perceptive” because she called TechCrunch’s tone “whiny”. :)

For the concert, I have engaged the services of two performers who are going to reenact a famous match between Garry Kasparov and IBM’s Deep Blue computer (shown below). My piece is called:

Kasparov vs. Deep Blue, 1997, Game 6

As the performers play this historically significant chess game, the first match in which the world human champion lost to a machine under tournament conditions, my musical chess system will analyze the moves, and you will hear the analysis. Since my own chess software is not nearly as good as Deep Blue, I have named it “Shallow Brown” — you figure it out! Coincidentally, “Shallow Brown” is also the title of a sea chanty (perhaps inspired by the bilge water being pumped while it was sung…).

There have been an enormous number of challenges involved in making this system work, and much work remains. While solving the myriad technical issues, I haven’t had much time to work on the musicality of this piece – but I have a few more weeks to go yet! With that disclaimer out of the way, I offer a brief audio sample of my chess engine, as it thinks about a chess position.

Shallow Brown – The Musical Chess Engine

Here’s a longer sample – about a minute from the middle of the Kasparov/Deep Blue game, after I did a little work on assigning different instruments to the two opponents.

Kasparov vs. Deep Blue, Excerpt

Kasparov gets mostly string sounds, and is heard more from the left channel. Deep Blue gets more mallet instruments, and is heard more from the right. I play the Deep Blue analysis a little deeper into the look-ahead tree, which produces more rapid-fire (and robotic-sounding) ostinati.

This piece is just one of a number of interesting new works, all inspired by machines of different kinds, to be performed, Friday Evening, June 26th in Los Angeles.

NewTown Presents
Cranks, Cams and Computers
New Machines, New Music
Friday, June 26

GLAD (Greater L.A. Agency on Deafness)
2222 Laverna Avenue,
Eagle Rock, CA 90041

Installations open 6:00PM
Performances at 8:00PM

Admission $10.00
$5.00 NewTown and Eagle Rock Center for the Arts members

Installations by
    Jim Bumgardner
    Carl Burmeister
    Joe Cantrell
    Daniel Corral
    Joe Potts
    Gary Raymond

Performances by
    Jim Bumgardner
    Carl Burmeister
    The Crank Ensemble
    Frank Pahl
    Gary Raymond

NewTown House Band
    Joe Berardi
    Lewis Keller
    Jessica Catron
    William Roper

Information:
    NewTown
    (626) 398-9278
    www.newtownarts.org
    info@newtownarts

Made possible by grants from Los Angeles County Board of Supervisors through the Los Angeles County Arts Commission, City of Los Angeles Department of Cultural Affairs and NewTown Members’ donations.

Here’s a Facebook Event Page I’ve set up for the concert.

I should mention that in addition to the chess piece, I’m also working on an installation of a number of my Whitney Music Boxes for this show.

So… if machines, cranks, cams, pianolas, and strange musical machines turn you on, and you’re going to be in the Los Angeles area — keep the evening of June 26th open!

UPDATE:

VENUE CHANGE

Due to circumstances beyond anyone’s control, there has been a last minute change of venue for Friday’s show, originally scheduled for Center for the Arts, Eagle Rock.

New Location:

GLAD (Greater L.A. Agency on Deafness)
2222 Laverna Avenue, Eagle Rock, CA 90041

This is just a few blocks away from the original location.

UPDATE:

Video of the performance can be viewed here.

I found this old video of mine while looking at some old backup CDs. Back in the early 90s, while playing with Gryphon Software’s “Morph” software, I accidentally stumbled upon a technique for making a still photograph or painting look like a hologram. The basic idea is that you make a mirror image of the photo, by flopping it horizontally in Photoshop. Then you morph from the original to the mirror image, using still-image morphing software, matching the left-eye to the flopped right-eye (which now looks like a left-eye), and so-on. The result is that the image in the photo looks like it is turning it’s head slightly, as you can see. There’s a point in the middle of the sequence where the face is completely symmetrical. One of my earliest tests of this method was done with an image of the Mona Lisa. It also works nicely with the portraits on currency.

So I found a supplier in the UK, called Grand Illusions. They actually carry two models, including one with a larger number of tines (20 tines covering a 2 1/2 octave diatonic range ). Naturally I got the big one, and a packet of extra blank strips. :)

Now I’m wondering if I can use my Mindstorms parts to build a Lego robot that will punch the holes and turn the crank, so I can automatically convert MIDI files to music box strips… We’ll see. Right now I’m just having fun making stripey patterns.

UPDATE

Well here’s my first hand-punched piece (aside from the stripey pattern shown above) : A little music box etude based on an old piano piece of mine. Took about an hour to plan and an hour to punch.

Music Box Etude #1

I found it helpful to place dots on the paper with a red marker first, so I didn’t have to do too much thinking about alignment when punching the holes. When I was done punching the holes, the table was littered with little notes.

Owner Jack Perron seems to offer a valuable formula for having a happy future: Find something you love that your friends think is a little weird. Pursue it with dogged determination. As a result of Jack’s passion for putting new music on old music boxes, he has developed a considerable amount of expertise on the subject. People come to him from the world over to get new discs for their beautiful machines. A little eccentrism is a good formula for success, don’t you think?

Icelandic singer/genius Björk came to him when she wanted to write some music box music for her 2001 album Vespertine. The track “Frosti,” from that album features a recording of one of Jack’s discs, specially made for Björk, and not only recorded for the album, but used on tour, and his discs appear elsewhere on the album as well. I didn’t know this until recently, and had assumed the recording was a digital synthesizer. Such is the effect that digital technologies have on the music industry. We recognize quality when we hear it, but we don’t know from whence the quality comes.

But the quality of Jack’s discs certainly shines through in this live performance, recorded at the Royal Opera House.

At the moment, Jack has been working with me to produce a disc by which I’ll be able to play a more tangible version of my composition Whitney Music Box (which people sometimes mistake for a historical recreation of a piece of John Whitney’s music- it’s actually a piece of Whitney’s motion graphics DNA that I have set to music.).

Jack has been absolutely wonderful to work with, and I hope he can cut a few Whitney-discs for other fans of the piece, something I am sure he’d be glad to do. The pattern on the discs is quite beautiful, although we’re both a bit worried that some antique music boxes may not be able to perform the piece in it’s entirety, because the first chord involves playing every tine on the jukebox at the same time, and most mechanical jukeboxes aren’t strong enough to manage it.

Look here for updates (and recordings!) of the progress of this fun little project, one of several I’m currently working on related to mechanical music.

I’m now working on composing some new music for an orchestrion. This will be no mere weekend-long project (as most of mine tend to be), and hopefully I can share some audio snippets with you as work progresses.

I imagine most of you don’t know what an orchestrion is. It’s a kind of automatic or mechanical music instrument that combines features found in other mechanical instruments to make a whole “orchestra”: piano, organ ranks and percussion. In the early 1920s, orchestrions were a relatively common component of dance halls and amusement arcades, but they, and most other automatic instruments were largely displaced by the economics of radio and higher quality recordings, which could deliver a greater variety of music much more inexpensively.

Most people associate the sound of orchestrions with carnivals, perhaps because antique carousel rides sometimes use them (or band organs, which are similar) to provide the music. They also tend to evoke “old timey” associations, because the type of music typically played on them often dates from the early 20th century. Here’s a sample:

I Want to be Happy, performed by SOFI, arranged by Craig Brougher

However, I have a strong (and quite possibly insane) belief that these associations are too narrow, and that the musical potential of these instruments is much wider. I believe they are capable of making less anachronistic sounds that can be more deeply felt by the listener. This is the counterpart to my belief that music composed by (or with the aid of) machines is capable of greater emotional affect in the listener than the dreck produced by Microsoft Songsmith or Band-in-a-Box.

As a long time practitioner of mechanical composing – that is, using machines as an aid to composition, I think the most appropriate performer for an automatic composition is an automatic instrument. To date, I’ve used computers a lot, but computers don’t have huge ranks of organ pipes and triangles.

There’s no denying that pretty much every Orchestrion recording I’ve heard is a little silly, and there’s nothing wrong with that! Seriousness, like utility, is overrated (see previous post on this subject).

The Orchestrion I’m composing for, SOFI, is the inspired creation of Craig Brougher, a mechanical instrument specialist who built her in Kansas City. SOFI can produce piano, organ, xylophone and various percussion sounds.

Amusingly, Craig and I have musical tastes that are from very different corners of the universe, but we both agree that Orchestrions are capable of far more than carnival novelties. I’ll be preparing MIDI scores here in Los Angeles, which Craig will test and record in Kansas City.

I’m planning a piece for SOFI that will contain (significantly more elaborate) versions of the visual-process-music techniques I developed for my Whitney Music Box and Wheel Music.

This music probably won’t be as pleasant to listen to as I would like it to be. This is one of the reasons I use visual animations with my music. I think the visuals help provide an explanation for what is going on, and help the ear anticipate what is going to come next.

“The ear tends to be lazy, craves the familiar and is shocked by the unexpected; the eye, on the other hand, tends to be impatient, craves the novel and is bored by repetition.”
W. H. Auden

My paraphrase of that quote is “The eye likes surprise but the ear likes comfort.”

My solution to that problem is to provide visual scores with my more complex music. I started this practice in college with a long tape loop piece called “Wound Room,” although at the time I didn’t have the means to synchronize the score display with the music. I don’t know if the technique works, but it certainly seems to have garnered my Whitney pieces more appreciative listeners than if I had simply released the audio tracks and explained them in words. People like a good show.

Combining visual process music with an orchestrion should make a fun, noisy, and anachronistic show! Sadly, Orchestrions are not exactly what you would call “portable,” but I’ll climb (or haul) that mountain when I get to it…

I thought it would be interesting to measure the level of activity, so I made a “Honeypot Bot” script, that uses the twitter account HoneyPotBot.

Every minute and a half, this bot recites a collection of words which come from a dictionary. In addition to common English words, the list includes celebrity names, the names of music acts, place names, and the names of all the companies in the S&P 500. Those words are the honey that attract the bots – scripts other people have written that are targetting certain keywords, or scripts that just auto-follow people at random.

I’ve been running the Honeypot Bot since March 26th, and as of this writing (March 31), it has collected 152 followers. If you look at the account, you’ll see fewer followers, because some of the accounts have been invalidated by twitter, and some have ‘unfollowed’ after a few hours.

If you look at the accounts, you’ll see that most of them have much bigger “following” lists than “follower” lists, which is a telltale sign of a auto-follower script at work. Looking at the lists of people these bots are following, you can identify the words the bots are interested in, which include

airplane
ballet
Beckett
Berlin
breakfast
Brisbane
chiropracter
cinema
coed
Deepak Chopra
Dr Phil
dressage
flexible
frugal
gallop
golf
harpo
kobayashi
moroccan
Oprah
poker
Ringo Starr
shoes
Whitest Boy Alive
Zend

…just to name a few.

Among the automatic followers are a network of chiropracters (I’ve been followed by eleven so far), who all appear to be based in different cities, but have identical looking webpages and twitter accounts – most with the same identical avatar – I assume they are all using the same marketing service for chiropracters.

Now, to be clear, my bot doesn’t show that there are only 152 auto-following bots on twitter. I imagine this is a mere fraction of the true total. The cleverer bots don’t follow on single words, like “chiropracter.” They combine words, like “need + chiropracter”. The problem with single words is that you really have no inkling about the context the word was used in.

For example, TheHobbyGuy is auto-following everyone who says “airplane” and “helicopter”. But why are those people saying those words? It could just as easily be to say “i wish the helicopter would stop flying over my house” as to say “I have an insatiable love of model helicopters”.

Clearly, OprahToday is not being very discriminating by following every person who mentions “Oprah,”, “Harpo” and “Dr. Phil.” How many of those people are fans of Harpo Marx, or complaining how Dr Phil is exploiting that crazy octuplet woman?

And unfortunately, those undiscriminating bots are going to ruin it for the discriminating ones that are trying to use more accurate targetting, and provide useful services. There are lots of folks jumping on the Twitter-marketing bandwagon right now, and these 152 undiscriminating auto-followers are just the tip of the iceberg. In a few months, the twitter spam problem is going to get significantly worse, and the signal-to-noise ratio much, much lower.