My thesis has quite a bit to do with language, and also quite a bit to do with codified binaries in society—about what or who is/not permitted and by whose authority, how language of policy slicks into the language of Terms & Conditions, which slicks right back into the meat sphere (because as it turns out the digital vs the corporeal is a binary). It's what encouraged me to take this class in the first place, not to mention the fact that Python is actually pretty fun.
I don't want to get into the nitty-gritty of my thesis here, but the part that drew me to Material of Language was thinking about stigma-based censorship/banning. I'm heading more toward creating more image-centric research at the end of the day, but have been thinking a lot about the glaring bias of what is considered "protected speech" vs "hate speech" on social media platforms, such as:
Both of these examples were reported. However, the first, which is quite obviously white nationalist speech, was considered protected, while the second, which is saying that maybe predators are the problem in the event that a woman is assaulted while wearing a skirt, not that she was "asking for it" by what she was wearing. It could be assumed that the perpetrator in reference is male. Therefore this was considered gender-based "hate-speech."
Hm.
So we all know that there are tag bans on certain words on the premise that they could potentially aggregate explicit content. Unfortunately many words used by marginalized communities are caught under a constantly-broadening scope of "obscenity" thereby codifying stigma into the machine. This banning has also unjustifiably punished those who are consensually (self)employed in sex trades for many reasons I won't get into here (it's my entire thesis), so I've been thinking of a potential for creating a poetic cryptography of sort for networked subversives and those at the margins. So these are the things influencing my work in this class for the semester.
Getting "stuck in my head"
Needless to say, the research for my thesis has been harrowing due to the severity of the topic, and my ability to think of a project that isn't burning the entire system down has been... rather difficult. My thesis advisor suggested that I'm getting "stuck in my head" which is a paradox since my topic is really about bodies, so I figured I'd use this first assignment to reconstruct my research into something less... wordy. My intention was to take my paper and see if I could interpret it into a music file, which I didn't achieve. But I got as far as composing a binary string that I hoped to encode into a WAV file, I feel like I either made an easy task more difficult, or that I'm one or two missing steps away from success. This is where we got to... First I uploaded and split my research paper, then I used the Counter PyPi to sort the list of words by frequency of use:
Obviously stop words are the most frequent, so I used the Natural Language Toolkit to identify and filter out English stop words:
I split the words into characters and then translated them into their numerical values
And finally created a binary string, which is as far as I got. I attempted a few different things for audio, but as noted couldn't figure out encoding... so I'm not sure if this is something to keep pursuing or just chalk this week up to a refresher course.
