How many people liked your last tweet? Oh yeah? Didja get any retweets? Was it enough to satisfy your need for acceptance, or were you disappointed by the Twitterverse’s reaction?
If you couldn’t see the number of likes, retweets, or followers you had, would you still even use Twitter?
[Ben Grosser] wants to know. He’s trying to see if people will look their relationship with social media squarely in the eye and think honestly about how it affects them. After all, social media itself isn’t the bad guy here—we are all responsible for our own actions and reactions. He’s created a browser extension that demetricates Twitter by removing any bluebird-generated quantifier on the page. It works for tweets, retweets, and the number of tweets playing the trending tag game. Numbers inside of tweets and on user profiles aren’t hidden, however, so you’ll still be able to see, for example, tweets containing Prince lyrics.
The Twitter Demetricator is available as a Chrome extension, and as a userscript for Tampermonkey for the other browsers people actually use (read: no IE support). Here’s what we want to know: Can he gamify it? Can he make a game out of weaning ourselves off of these meaningless metrics and inflated sense of self and FOMO and whatever marketing guff they come up with next to describe the modern human condition? We’re getting low on dopamine over here.
This isn’t [Ben]’s first foray into the social aspects of social media. We covered his Facebook demetricator way back in ’12.
Twitter is kind of a crazy place. World leaders doing verbal battle, hashtags that rise and fall along with the social climate, and a never ending barrage of cat pictures all make for a tumultuous stream of consciousness that runs 24/7. What exactly we’re supposed to do with this information is still up to debate, as Twitter has yet to turn it into a profitable service after over a decade of operation. Still, it’s a grand experiment that offers a rare glimpse into the human hive-mind for anyone brave enough to dive in.
One such explorer is a security researcher who goes by the handle [x0rz]. He’s recently unveiled an experimental new piece of software that grabs Tweets and uses them as a “noise” to mix in with the Linux urandom entropy pool. The end result is a relatively unpredictable and difficult to influence source of random data. While he cautions his software is merely a proof of concept and not meant for high security applications, it’s certainly an interesting approach to introducing humanity-derived chaos into the normally orderly world of your computer’s operating system.
This hack is made possible by the fact that Twitter offers a “sample” function in their API, which effectively throws a randomized collection of Tweets at anyone who requests it. There are some caveats here, such as the fact that if multiple clients request a sample at the same time they will both receive the same Tweets. It’s also worth mentioning that some characters are unusually likely to make an appearance due to the nature of Twitter (emoticons, octothorps pound signs, etc), but generally speaking it’s not a terrible way to get some chaotic data on demand.
On its own, [x0rz] found this data to be a good but not great source of entropy. After pulling a 500KB sample, he found it had an entropy of 6.5519 bits per byte (random would be 8). While the Tweets weren’t great on their own, combining the data with the kernel’s entropy pool at /dev/urandom provided something that looked a lot less predictable.
The greatest weakness of using Twitter as a source of entropy is, of course, the nature of Twitter itself. A sufficiently popular hashtag on the rise might be just enough to sink your entropy. It’s even possible (though admittedly unlikely) that enough Twitter spam bots could ruin the sample. But if you’re at the point where you think hinging your entropy pool on a digital fire hose of memes and cat pictures is sufficient, you’re probably not securing any national secrets anyway.
(Editor’s note: The way the Linux entropy pool mixes it together, additional sources can only help, assuming they can’t see the current state of your entropy pool, which Twitter cats most certainly can’t. See article below. Also, this is hilarious.)
How quickly would you say yes to being granted the power to control lightning? Ok, since that has hitherto been impossible, what about the lesser power of detecting and tweeting any nearby lightning strikes?
Tingling at the possibility of connecting with lightning’s awesome power in one shape or another, [Hexalyse] combined AMS’s lightning sensor chip with a Raspberry Pi and a whipped up a spot of Python code to tweet the approach of a potential storm. Trusting the chip to correctly calculate strike data, [Hexalyse]’s detector only tweets at five minute intervals — because nobody likes a spambot — but waits for at least five strikes in a given time frame before announcing that a storm’s-a-brewing. Each tweet announces lightning strike energy, distance from the chip, and number of strikes since the last update. If there haven’t been any nearby lightning strikes for an hour, the twitter feed announces the storm has passed.
It just so happened that as [Hexalyse] finished up their project, a thunderstorm bore down on their town of Toulouse, France putting their project to the test — to positive success. Check out the detector’s tweets (in French).
Even with all the hamster wheel trackers out there (and on this site) there’s room for improvement. [Bogdan] upgraded his hamster wheel from an Arduino and datalogging shield to an ESP32, and unleashed some new capabilities one does not ordinarily associate with hamster wheels.
[Bogdan]’s project logs distance in feet, duration of current session in time, RPM, overall revolutions, speed in MPH, and overall number of sessions, as well as a couple of system monitoring stats. It also tracks multiple wheels, as [Piontek] (the hamster) has two. However, thanks to the ESP32, [Bogdan]’s wheel tracker tweets its stats and updates a ThingSpeak dashboard with [Piontek]’s workouts.
In addition to its functionality, [Bogdan] made a point to make the project look and feel FINISHED. He designed custom 3D parts including a front plate, hooks for attaching the control box to the cage, and mounts for attaching the sensor to the wheel.
Grab a shortwave radio, go up on your roof at night, turn on the radio, and if the ionosphere is just right, you’ll be able to tune into some very, very strange radio stations. Some of these stations are just a voice — usually a woman’s voice — simply counting. Some are Morse code. All of them are completely unintelligible unless you have a secret code book. These are number stations, or radio stations nobody knows much about, but everyone agrees they’re used to pass messages from intelligence agencies to spies in the field.
A few years ago, we took a look at number stations, their history, and the efforts of people who document and record these mysterious messages used for unknown purposes. These number stations exist for a particular reason: if you’re a spy, you would much rather get caught with an ordinary radio instead of a fancy encryption machine. Passing code through intermediaries or dead drops presents a liability. The solution to both these problems lies in broadcasting messages in code, allowing anyone to receive them. Only the spy who holds a code book — or in the case of the Cuban Five, software designed to decrypt messages from number stations — can decipher the code.
Number stations are a hack, of sorts, of the entire concept of broadcasting. For all but a few, these number stations broadcast complete gibberish. Only to the person holding the code book or the decryption software do these number stations mean anything. However, since the first number stations went on the air over one hundred years ago, broadcasting has changed dramatically. We now have the Internet, and although most web services cannot be considered a one-to-many distribution as how broadcasting is defined, Twitter can. Are there number stations on Twitter? There sure are. Are they used by spies or agents of governments around the world? That’s a little harder to say.
[Ashley Feinberg] is not one to say no to a challenge. When James Comey (the current Director of the Federal Bureau of Investigation for the United States of America) let slip that he has a secret Twitter and Instagram account, [Ashley] knew what she had to do.
At the beginning, [Ashley] knew only a few things: (1) Comey had recently joined twitter and (2) he only allows his “immediate relatives and one daughter’s serious boyfriend” to follow him. As such, [Ashely] deduced that “if we can find the Instagram accounts belonging to James Comey’s family, we can also find James Comey.”
To start, [Ashley] found the Instagram account of Comey’s 22-year-old son, a basketball star at Kenyon College. Not phased by Brien’s locked down Instagram account, [Ashley] requested access to Brien’s account in order to access the “Suggested for You” selections that are algorithmically generated from Brien Comey’s account. Sifting through the provided accounts [Ashley] found one that fit Comey’s profile: locked down with few friends. That account was named reinholdniebuhr. Not sure it was, in fact, James Comey, [Ashley] found Comey’s senior thesis on theologian Reinhold Niebuhr and televangelist Jerry Falwell as verification.
[Robin Bussell]’s NixieBot is a mash up of new age electronics and retro vintage components and he’s got a bunch of hacks crammed in there. It’s a Nixie tube clock which displays tweets, takes pictures of the display when it encounters tweets with a #NixieBotShowMe hash tag, and then posts requested pictures back to twitter. If a word is eight characters, it takes a snapshot. If it’s a longer message, NixieBot takes a series of pictures of each word, converts it to an animated GIF, and then posts the tweet. In between, it displays random tweets every twenty seconds. You can see the camera setup in the image below and you should check out the @nixiebot twitter feed to see some of the action.
For the display, he’s using eight big vintage Burroughs B7971 Nixie Tubes. These aren’t easy to source, and current prices hover around $100 each if you can find them. The 170V DC needed to run each tube comes from a set of six 12V to 170V converter boards specifically designed to drive these tubes. Each board can drive at least a couple of nixies, so [Robin]’s able to use just four boards for the eight tubes. Each nixie is driven by its own “B7971 SmartSocket“, a dedicated PIC16F690 micro-controller board custom designed for the purpose. A serial protocol makes it easy to daisy-chain the SmartSockets to build multi character displays.