Remembering the time that an article in the Daily Caller took a colleague’s research out of context to make it look bad, but because it tripped a Google Alert, it still got included in some “our research in the media!” newsletter.

Last week, I read a post from Andrew Heiss on Bluesky that inspired me to take a look at whether/where I was cited on any Wikipedia articles. I knew my research had been referenced on one particular page, but I’d never done a thorough search for this and decided to give it a whirl. While I can’t claim anything as cool as the page on Hosni Mubarak (where Andrew’s research is cited), my research is referenced on three different Wikipedia articles, which feels pretty cool, actually.

I’m a big fan of the 404 Media tech news outlet, and I also really enjoy their podcast. I especially appreciated an episode that I listened to yesterday, which I’m embedding below as a YouTube video (as an aside, I simply do not understand how YouTube has become a major podcast-listening medium, so it pains me a bit to do this, but I’m once again trying to write something quickly before getting to real work, and YouTube embeds are relatively easy to do in Hugo, so that’s what I’m going with.

A couple of years ago, I worked with a graduate student to examine the geographic and linguistic diversity in an online Community of Christ ministry that made an intentional effort to cross borders during the COVID-19 pandemic (and before and since, but for all of the obvious reasons, this was particularly pronounced during the pandemic). I was pleased with how the work went and was eager to get it to publication.

Today was really, truly going to be a much-needed writing day, and then I didn’t even clear my inbox until 2:30. Yayyyyyy.

This morning on Bluesky, I saw some posts about a class action lawsuit against Anthropic for their use of pirated, copyrighted materials in training their generative AI models. One of the sources of these copyrighted materials was the LibGen database, which I took a peek at nearly six months ago to confirm what I was already sure to be true: that my scientific writing was also collected as training material by companies like Anthropic or Meta.

Love that moment in academic writing where you can find five rejected versions of a paragraph below the version I’m currently working on.

This sounds fine.

Le décryptage des communautés en ligne a toujour été un genre important des recherches, mais c’est surtout important dans des cas comme celui-ci.

I can see the value in some state guidelines, but I suspect they would be more permissive than what I want for my classroom. I hope I’ll still have the chance to establish restrictions as I see fit.

Reading this through an Ellulian lens is interesting. In the 1950s, he was expressing concern about the valuing of (applied) technique over (basic) science. In this article, though, it’s clear how often that basic science is still described and defended in applied/technical terms. pushing the boundaries of knowledge seems to only be valuable if it “sow[s] practical spinoffs and breakthroughs” or helps the U.S. in its geopolitical competition. Gift link.

Dealing with yet another case of “these reviewer suggestions are good and pretty straightforward, so why don’t I have any motivation to make the revisions?”

Si on doit absolument investir au niveau national dans l’IA, je préfère cette approche (investir dans les recherches).

I’ve repeatedly referenced 20th century French technology scholar Jacques Ellul on my blog(s) since the beginning of the year. While my interest in Ellul’s work is also personal and political, I wrote back in February that one of the main reasons I’m reading a lot of Ellul right now is to add a stronger theoretical foundation to my scholarly work. With that context in mind, I’m happy to share that my first Ellul-inspired article has just been published in the Journal of Computing and Higher Education!

That feeling when you write an article for a lesser journal’s special issue but actually find a home in a stronger journal after the special editors reject it.

I’m pleased to be able to finally share the publication in the British Journal of Educational Technology of an article that Dan Krutka and I have been working on for some time, which documents activity in a teachers’ group on a far-right social media platform (which we intentionally don’t identify within the paper). Here’s a link to a full-text, read-only version of the article, and here’s the abstract as a preview:

One of the most frustrating experiences I’ve ever had with a journal appears to be coming to a happy conclusion, and that’s not a bad way to start a Monday.

I don’t personally need research funding, but I work in an academic ecosystem that’s highly dependent on it. Things aren’t looking good.

Last month, I wrote on both my reading up on Jacques Ellul and on concerns about how we understand the purpose and value of research. I’m continuing to read—or, rather, listen to—Ellul’s The Technological Society, and I was interested to find a passage that brought together these two ideas. Here’s Ellul, writing in the mid-twentieth century: We have already examined the requirement of immediate applicability; here we meet it again on the state level.

Thanks to this article from The Atlantic that I saw on Bluesky, I’ve been able to confirm something that I’ve long assumed to be the case: that my creative and scholarly work is being used to train generative AI tools. More specifically, I used the searchable database embedded in the article to search for myself and find that at least eight of my articles (plus two corrections) are available in the LibGen pirate library—which means that they were almost certainly used by Meta to train their Llama LLM.

In the past 24 hours, I’ve seen two different CFPs that apply perfectly to a paper I wrote and then abandoned after a rejection and a paper I’ve wanted to write but had no good reason to. This may be what gets me back into a research groove this semester.

My stress and anxiety levels have been high ever since the second Trump administration began and immediately started taking an axe to all sorts of things that one should not take an axe to. For admittedly selfish reasons, though, I’ve been particularly anxious since Friday, when the NIH announced that it was dramatically cutting its support to universities (and other research institutions) in the form of indirect costs. I don’t do NIH-funded work, but we’re a very medically focused campus, and there’s no way that the $40 million that the University estimates we could lose over the next year isn’t going to have ripple effects across campus (not to mention the fact that my colleagues in the College of Communication and Information regularly look to the NIH as a source of funding health communication research).

Me, all of December: “Next semester, I have a course release and a once-a-week evening class. I’m going to get so much research done during the day!” Me, on February 7th: “Wow, it’s great to finally be getting to research this semester.”

I’m proud of the research I’ve done on online communities taking cues from dark corners of the internet, and I’m glad that some reporters find it interesting. It’s still uncomfortable to read certain excerpts from my data out loud to people over the phone.

Reread some feedback from a journal editor after a couple of days, and while I still disagree with it, it’s at least more reasonable than I remembered it being.

For the past couple of years, my colleague Dr. Meghan Dowell and I have been working on a paper on students’ awareness of what data the Canvas learning management system collects (and subsequently makes available to certain stakeholders). I’m a fan of Nick Proferes’s paper [Information Flow Solipsism in an Exploratory Study of Beliefs About Twitter] and have long wanted to do something similar related to LMSs. This is even more Meghan’s area of specialty than mine, though, so I was grateful that she was also interested in the subject and took the lead in turning this idea into reality.

I love having a co-author who can provide the theoretical framing to turn my weird data from a dark corner of the internet into an interesting argument.

Back in 2020-2021, I made the decision to pivot from Twitter as a research site in case data ever became less available—and so I could focus more on right-wing online spaces. It was a good call but still hilariously mistaken at the same time.

Before writing what I want to write, I want to make a few things clear. Teaching is an important and noble profession, I love being a teacher, and it’s possible (and often easy) to distinguish between better and worse ways of teaching. With that out of the way, I want to start off this post by arguing that teaching is less of “a thing” than learning is. That is, learning is the real phenomenon here, and teaching is sort of an auxiliary practice that aims to support learning but can’t ever quite be the same thing.

That feeling when data you’re coding is just so bizarre that you don’t know what to make of it. Online communities are a heck of a thing to study.

What a gross offer to receive.

I usually do too much qualitative work for them to be useful, but .Rmd-based slides are a delight to work in.

I have conflicted feelings about productivity books, but even as I increasingly reject the emphasis on productivity, I do find that there are some gems in these books that are helpful to me as I try to keep my life organized across all of its dimensions. While rereading one of these books over the summer, I came across the following quote (which appears to be a misquotation of Oliver Wendell Holmes, Jr.

I keep thinking about the similarity of exploitation of academic labor by publishers to the exploitation of everyone’s labor by AI companies, and stories like this just make it more clear.

I dedicated most of my early career to Twitter and probably owe my tenure to the ease of collecting Twitter data once upon a time. Were it not for some timely decisions to diversify what platforms I was looking at, the API cutoff documented in this book would have really messed me up. Because of how important Twitter was to me professionally, I followed a lot of this news as it was happening.

Interesting read wirh important implications for how we think about research quality.