Digifesto

Tag: twitter

fancier: scripts to help manage your Twitter account, in Python

My Twitter account has been a source of great entertainment, distraction, and abuse over the years. It is time that I brought it under control. I am too proud and too cheap to buy a professional grade Twitter account manager, and so I’ve begun developing a new suite of tools in Python that will perform the necessary tasks for me.

I’ve decided to name these tools fancier, because the art and science of breeding domestic pigeons is called pigeon fancying. Go figure.

The project is now available on GitHub, and of course I welcome any collaboration or feedback!

At the time of this writing, the project has only one feature: it searches through who you follow on Twitter, finds which accounts are both inactive in 90 days and don’t follow you back, and then unfollows them.

This is a common thing to try to do when grooming and/or professionalizing your Twitter account. I saw a script for this shared in a pastebin years ago, but couldn’t find it again. There are some on-line services that will help you do this, but they charge a fee to do it at scale. Ergo: the open source solution. Voila!

becoming a #seriousacademic

I’ve decided to make a small change to my on-line identity.

For some time now, my Twitter account has been listed under a pseudonym, “Gnaeus Rafinesque”, and has had a picture of a cat. Today I’m changing it to my full name (“Sebastian Benthall”) and a picture of my face.

Gnaeus Rafinesque

Serious academic

I chose to use a pseudonym on Twitter for a number of reasons. One reason was that I was interested in participant observation in an Internet subculture, Weird Twitter, that generally didn’t use real names because most of their activity on Twitter was very silly.

But another reason was because I was afraid of being taken seriously myself. As a student, even a graduate student, I felt it was my job to experiment, fail, be silly, and test the limits of the media I was working (and playing) within. I learned a lot from this process.

Because I often would not intend to be taken seriously on Twitter, I was reluctant to have my tweets associated with my real name. I deliberately did not try to sever all ties between my Twitter account and my “real” identity, which is reflected elsewhere on the Internet (LinkedIn, GitHub, etc.) because…well, it would have been a lot of futile work. But I think using a pseudonym and a cat picture succeeded in signalling that I wasn’t putting the full weight of my identity, with the accountability entailed by that, into my tweets.

I’m now entering a different phase of my career. Probably the most significant marker of that phase change is that I am now working as a cybersecurity professional in addition to being a graduate student. I’m back in the working world and so in a sense back to reality.

Another marker is that I’ve realized that I’ve got serious things worth saying and paying attention to, and that projecting an inconsequential, silly attitude on Twitter was undermining my ability to say those things.

It’s a little scary shifting to my real name and face on Twitter. I’m likely to censor myself much more now. Perhaps that’s as it should be.

I wonder what other platforms are out there in which I could be more ridiculous.

things I’ve been doing while not looking at twitter

Twitter was getting me down so I went on a hiatus. I’m still on that hiatus. Instead of reading Twitter, I’ve been:

  • Reading Fred Turner’s The Democratic Surround. This is a great book about the relationship between media and democracy. Since a lot of my interest in Twitter has been because of my interest in the media and democracy, this gives me those kinds of jollies without the soap opera trainwreck of actually participating in social media.
  • Going to arts events. There was a staging of Rhinoceros at Berkeley. It’s an absurdist play in which a small French village is suddenly stricken by an epidemic wherein everybody is transformed into a rhinoceros. It’s probably an allegory for the rise of Communism or Fascism but the play is written so that it’s completely ambiguous. Mainly it’s about conformity in general, perhaps ideological conformity but just as easily about conformity to non-ideology, to a state of nature (hence, the animal form, rhinoceros.) It’s a good play.
  • I’ve been playing Transistor. What an incredible game! The gameplay is appealingly designed and original, but beyond that it is powerfully written an atmospheric. In many ways it can be read as a commentary on the virtual realities of the Internet and the problems with them. Somehow there was more media attention to GamerGate than to this one actually great game. Too bad.
  • I’ve been working on papers, software, and research in anticipation of the next semester. Lots of work to do!

Above all, what’s great about unplugging from social media is that it isn’t actually unplugging at all. Instead, you can plug into a smarter, better, deeper world of content where people are more complex and reasonable. It’s elevating!

I’m writing this because some time ago it was a matter of debate whether or not you can ‘just quit Facebook’ etc. It turns out you definitely can and it’s great. Go for it!

(Happy to respond to comments but won’t respond to tweets until back from the hiatus)

more on algorithms, judgment, polarization

I’m still pondering the most recent Tufekci piece about algorithms and human judgment on Twitter. It prompted some grumbling among data scientists. Sweeping statements about ‘algorithms’ do that, since to a computer scientist ‘algorithm’ is about as general a term as ‘math’.

In later conversation, Tufekci clarified that when she was calling out the potential problems of algorithmic filtering of the Twitter newsfeed, she was speaking to the problems of a newsfeed curated algorithmically for the sake of maximizing ‘engagement’. Or ads. Or, it is apparent on a re-reading of the piece, new members. She thinks an anti-homophily algorithm would maybe be a good idea, but that this is so unlikely according to the commercial logic of Twitter to be a marginal point. And, meanwhile, she defends ‘human prioritizatin’ over algorithmic curation, despite the fact that homophily (not to mention preferential attachment) are arguable negative consequences of social system driven by human judgment.

I think inquiry into this question is important, but bound to be confusing to those who aren’t familiar in a deep way with network science, machine learning, and related fields. It’s also, I believe, helpful to have a background in cognitive science, because that’s a field which maintains that human judgment and computational systems are doing fundamentally commensurable kinds of work. When we think in sophisticated way about crowdsourced labor, we use this sort of thinking. We acknowledge, for example, that human brains are better at the computational task of image recognition, so then we employ Turkers to look at and label images. But those human judgments are then inputs to statistical processes that verify and check those judgments against each other. Later, those determinations that result from a combination of human judgment and algorithmic processing could be used in a search engine–which returns answers to questions based on human input. Search engines, then, are also a way of combining human and purely algorithmic judgment.

What it comes down to is that virtually all of our interactions with the internet are built around algorithmic affordances. And these systems can be understood systematically if we reject the quantitative/qualitative divide at the ontological level. Reductive physicalism entails this rejection, but–and this is not to be understated–pisses or alienates people who do qualitative or humanities research.

This is old news. C.P. Snow’s The Two Cultures. The Science Wars. We’ve been through this before. Ironically, the polarization is algorithmically visible in the contemporary discussion about algorithms.*

The Two Cultures on Twitter?

It’s I guess not surprising that STS and cultural studies academics are still around and in opposition to the hard scientists. What’s maybe new is how much computer science now affects the public, and how the popular press appears to have allied itself with the STS and cultural studies view. I guess this must be because cultural anthropologists and media studies people are more likely to become journalists and writers, whereas harder science is pretty abstruse.

There’s an interesting conflation now from the soft side of the culture wars of science with power/privilege/capitalism that plays out again and again. I bump into it in the university context. I read about it all the time. Tufekci’s pessimism that the only algorithmic filtering Twitter would adopt would be one that essentially obeys the logic “of Wall Street” is, well, sad. It’s sad that an unfortunate pairing that is analytically contingent is historically determined to be so.

But there is also something deeply wrong about this view. Of course there are humanitarian scientists. Of course there is a nuanced center to the science wars “debate”. It’s just that the tedious framing of the science wars has been so pervasive and compelling, like a commercial jingle, that it’s hard to feel like there’s an audience for anything more subtle. How would you even talk about it?

* I need to confess: I think there was some sloppiness in that Medium piece. If I had had more time, I would have done something to check which conversations were actually about the Tufekci article, and which were just about whatever. I feel I may have misrepresented this in the post. For the sake of accessibility or to make the point, I guess. Also, I’m retrospectively skittish about exactly how distinct a cluster the data scientists were, and whether its insularity might have been an artifact of the data collection method. I’ve been building out poll.emic in fits mainly as a hobby. I built it originally because I wanted to at last understand Weird Twitter’s internal structure. The results were interesting but I never got to writing them up. Now I’m afraid that the culture has changed so much that I wouldn’t recognize it any more. But I digress. Is it even notable that social scientists from different disciplines would have very different social circles around them? Is the generalization too much? And are there enough nodes in this graph to make it a significant thing to say about anything, really? There could be thousands of academic tiffs I haven’t heard about that are just as important but which defy my expectations and assumptions. Or is the fact that Medium appears to have endorsed a particular small set of public intellectuals significant? How many Medium readers are there? Not as many as there are Twitter users, by several orders of magnitude, I expect. Who matters? Do academics matter? Why am I even studying these people as opposed to people who do more real things? What about all the presumably sane and happy people who are not pathologically on the Internet? Etc.