I’m co-organising a preconfernece workshop for AoIR2022 in Dublin today with Annette Markham and MaryElizabeth Luka today, and I’m going to show a few of the ways I’ve engaged with new digital platforms and genres over the years. This is a key research methodology for me. For this particular workshop I’ll focus on blogs, Snapchat, TikTok and Wikipedia.

I started blogging more than twenty years ago, on October 9, 2000, and many of my posts reflect upon the practice of blogging (I also published research on blogging, including the first paper on it, written with Torill Mortensen in 2002, a book chapter from 2006 on how much harder I found it to blog when a professor compared to when I was a PhD student, and of course a book on blogging as well). One old blog post I often return to was in response to another blog researcher who had written about blogs as a way of documenting research. Her post sounded reasonable, but something irked me about it, and as I thought through typing (as I did in my more active blogging days) I realised that blogging for me is about doing research and reflecting for myself and with others, not about documentation. Here is the post I wrote about that. I should blog more, eh?

Another genre I explored was Snapchat.

Next I discovered musical.ly, which was later bought by ByteDance and merged into TikTok. I had to learn how to do the TikTok dances, and the hand signs that are part of them absolutely fascinated me. Here’s a blog post about that, and I also published a paper on it. But to do that, I had to try to learn how to do the hand signs!

Casey Fiesler was a remote co-organiser of our workshop, and showed an AMAZING video summarising her experience making research videos on TikTok. (I’ll add a link if she makes it public) Casey’s TikToks are wonderful, you should check her out! An interesting point, if you’re into reducing bias in academia, is that the gender distribution is entirely different on TikTok and YouTube. Casey had been making videos on YouTube about how to get into PhD programs, but switched to TikTok when she realised how much greater her reach was there, and how well the TikTok algorithm did at getting her videos to the right people.

One of the genres I’m currently exploring is Wikipedia, where editing – and having my edits reverted and articles deleted – has taught me a lot about this genre. I’ve been editing pages for scholarly concepts, like media events, and for works of electronic literature or digital art I want to see documented, like Caitlin Fisher’s These Waves of Girls, and I’ve learned some of the strategies you need. Wikipedia is known for its gender bias, and I’ve also found it doesn’t document digital art or other non-institutionalised genres, largely because the standard rules state that art is notable if it’s in a major museum, which digital art usually isn’t because it’s on the internet. So Wikipedia – and thus also Wikidata which underpins much of the semantic web – is blind to digital art. By paying attention to and participating in Wikipedia’s Articles for deletion (AfD) debates (after having several articles deleted) I’ve figured out how to demonstrate that digital art or electronic literature is notable: cite sources profusely, find reviews and discussions in scholarly papers, examples of the work being taught at a university. Focus on making articles the works, then add articles about the artists, who may not be notable in themselves by Wikipedia standards (are there three feature articles about them (not just about their work) in mainstream media?) but are by definition notable if they have created 2-3 notable works. Maybe I’ll write a separate blog post on that some day, but for now, I just want to say that the Wikipedia too is a genre that is best learnt and best understood by writing and creating in the genre.

My paper Speculative Interfaces makes a similar argument to this, but about how works of electronic literature and digital humanities projects are examples of developing knowledge and genres by experimenting with the interface, with the materiality and form of the genre. New ways of thinking can require new genres and new interfaces.

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The Machine Vision in Everyday Life project invites proposals for an interdisciplinary workshop using qualitative approaches and digital methods to analyse how machine vision is represented in art, science fiction, games, social media and other forms of cultural and aesthetic expression.