#socialmediaforacademics — Public Fediverse posts

Why I don’t like recording events

I was asked earlier why I don’t like recording events and realised I’d never actually written it down. There are a few reasons I feel increasingly strongly about this:

• We have started to record academic events by default and I think that is fundamentally problematic in principle
• There’s an assumption that the ease with which we can record online events means we should record them and I just don’t get why that is
• There’s a fundamental value in the academic event as something that brings people together synchronously which recording undercuts
• The biggest problem with online events is passive engagement and (automatic) recording of them fits into that structure
• The quality of engagement should be more important than the quantity in most cases. What matters is how richly a core audience engages and there are trade offs which we need to recognise.
• Recording undermines the space for intellectual improvisation and risk taking
• The evidence I’ve seen (as someone who ran a lot of academic social media for a long time) is that engagement rates with event recording is very slow.
• My hunch is that the request for a recording often tracks a fear of missing out as much as it does a deliberate intention to engage with the recording

I’m not saying never record events. Clearly this serves a purpose in some cases. But we should only record events when we are clear about the rationale for doing so.

#academicEvents #conferences #digitalScholarship #onlineVideo #publicScholarship #seminars #socialMediaForAcademics #workshops #zoom

Why I don’t like recording events

I was asked earlier why I don’t like recording events and realised I’d never actually written it down. There are a few reasons I feel increasingly strongly about this:

• We have started to record academic events by default and I think that is fundamentally problematic in principle
• There’s an assumption that the ease with which we can record online events means we should record them and I just don’t get why that is
• There’s a fundamental value in the academic event as something that brings people together synchronously which recording undercuts
• The biggest problem with online events is passive engagement and (automatic) recording of them fits into that structure
• The quality of engagement should be more important than the quantity in most cases. What matters is how richly a core audience engages and there are trade offs which we need to recognise.
• Recording undermines the space for intellectual improvisation and risk taking
• The evidence I’ve seen (as someone who ran a lot of academic social media for a long time) is that engagement rates with event recording is very slow.
• My hunch is that the request for a recording often tracks a fear of missing out as much as it does a deliberate intention to engage with the recording

I’m not saying never record events. Clearly this serves a purpose in some cases. But we should only record events when we are clear about the rationale for doing so.

#academicEvents #conferences #digitalScholarship #onlineVideo #publicScholarship #seminars #socialMediaForAcademics #workshops #zoom

Why I don’t like recording events

I was asked earlier why I don’t like recording events and realised I’d never actually written it down. There are a few reasons I feel increasingly strongly about this:

• We have started to record academic events by default and I think that is fundamentally problematic in principle
• There’s an assumption that the ease with which we can record online events means we should record them and I just don’t get why that is
• There’s a fundamental value in the academic event as something that brings people together synchronously which recording undercuts
• The biggest problem with online events is passive engagement and (automatic) recording of them fits into that structure
• The quality of engagement should be more important than the quantity in most cases. What matters is how richly a core audience engages and there are trade offs which we need to recognise.
• Recording undermines the space for intellectual improvisation and risk taking
• The evidence I’ve seen (as someone who ran a lot of academic social media for a long time) is that engagement rates with event recording is very slow.
• My hunch is that the request for a recording often tracks a fear of missing out as much as it does a deliberate intention to engage with the recording

I’m not saying never record events. Clearly this serves a purpose in some cases. But we should only record events when we are clear about the rationale for doing so.

#academicEvents #conferences #digitalScholarship #onlineVideo #publicScholarship #seminars #socialMediaForAcademics #workshops #zoom

Why I don’t like recording events

I was asked earlier why I don’t like recording events and realised I’d never actually written it down. There are a few reasons I feel increasingly strongly about this:

• We have started to record academic events by default and I think that is fundamentally problematic in principle
• There’s an assumption that the ease with which we can record online events means we should record them and I just don’t get why that is
• There’s a fundamental value in the academic event as something that brings people together synchronously which recording undercuts
• The biggest problem with online events is passive engagement and (automatic) recording of them fits into that structure
• The quality of engagement should be more important than the quantity in most cases. What matters is how richly a core audience engages and there are trade offs which we need to recognise.
• Recording undermines the space for intellectual improvisation and risk taking
• The evidence I’ve seen (as someone who ran a lot of academic social media for a long time) is that engagement rates with event recording is very slow.
• My hunch is that the request for a recording often tracks a fear of missing out as much as it does a deliberate intention to engage with the recording

I’m not saying never record events. Clearly this serves a purpose in some cases. But we should only record events when we are clear about the rationale for doing so.

#academicEvents #conferences #digitalScholarship #onlineVideo #publicScholarship #seminars #socialMediaForAcademics #workshops #zoom

Why I don’t like recording events

I was asked earlier why I don’t like recording events and realised I’d never actually written it down. There are a few reasons I feel increasingly strongly about this:

• We have started to record academic events by default and I think that is fundamentally problematic in principle
• There’s an assumption that the ease with which we can record online events means we should record them and I just don’t get why that is
• There’s a fundamental value in the academic event as something that brings people together synchronously which recording undercuts
• The biggest problem with online events is passive engagement and (automatic) recording of them fits into that structure
• The quality of engagement should be more important than the quantity in most cases. What matters is how richly a core audience engages and there are trade offs which we need to recognise.
• Recording undermines the space for intellectual improvisation and risk taking
• The evidence I’ve seen (as someone who ran a lot of academic social media for a long time) is that engagement rates with event recording is very slow.
• My hunch is that the request for a recording often tracks a fear of missing out as much as it does a deliberate intention to engage with the recording

I’m not saying never record events. Clearly this serves a purpose in some cases. But we should only record events when we are clear about the rationale for doing so.

#academicEvents #conferences #digitalScholarship #onlineVideo #publicScholarship #seminars #socialMediaForAcademics #workshops #zoom

📱🚫 On withdrawal from social media

https://www.youtube.com/watch?v=16izdtkzEz8

In less than twenty four hours my book Platform and Agency: Becoming Who We Are will be released. In an important sense I worked on this book for fifteen years, beginning with my part-time PhD in 2008 and ending with the initial phase of my LLM research in 2023. I feel ambivalent about it in a number of ways. I somehow conspired to rush it despite the fact I worked on it for well over a decade. I let an utterly avoidable crisis of intellectual confidence derail it in the later years of the 2010s. I didn’t get the chance to ask Maggie Archer to write a forward to it. I somehow dropped the ball and agreed to a £35 eBook and £116 hardback which means I wouldn’t buy it myself. Rather than enter a third year of negotiation with the publisher I pushed it over the finish line when it still wasn’t quite in the shape I wanted to get it into. Frankly I needed to move on with my life and completing Platform and Agency enabled me to do it in a whole range of ways.

It still feels like a significant occasion though. It’s my fourth monograph, fifth if you count the second edition of Social Media for Academics which was basically a rewrite from scratch. It’s the tenth book I’ve published overall. This makes it feel less significant in the sense that I’ve released five books in the last five years and the novelty is wearing off. What makes it feel special is that this book, for all its flaws, has a radical originality which other things I’ve written or edited lack. It captures a specific way of making sense of the role of technology in the social world, which I’ve been monomaniacally pursuing ever since I realised how significant bulletin boards were to my teenage years. It offers a genuinely original way of making sense of how platforms influence how we became who we are, including what this process of becoming entails in psychosocial terms. I’ll leave it to readers to decide if it’s useful or interesting. But it’s certainly intellectually unique. It captures what I think is a coherent social ontology underpinning the bizarre range of topics I’ve worked on over the course of my career.

Hence the vague desire to shout about it. Look look I did a book! I did a big theory book! Even if it’s much smaller big book than planned because pragmatism, a concern for my own well-being and the publisher’s reticence meant I dropped a couple of chapters from the plan. I would sincerely like anyone who’s interested to know this book exists so they are more likely to read it. I would like anyone who has expressed curiosity about my research agenda to at least skim the book because it’s the most foundational answer to the question “what do you research?” I’m ever likely to produce. But I realised this evening as I was psyching myself up for a joyless engagement with social media that I don’t want these things enough to reenter the Twittering Machine.

I can see the costs involved in not shouting about this book (or the three papers I’ve had published recently) but I just don’t care enough to want to reactive my Bluesky account or log into Linkedin for the first time in months. I last posted on Linkedin almost six months ago and I’m suddenly wondering if I’ll ever post on it again. Or any other social media for the matter. I just feel such a vivid aversion when I contemplate logging into these platforms again that I’m wondering what, if anything, would prompt me to do it. I feel a precarious sense of clarity about my life (and my work) which the rhythms of social media now appear profoundly threatening to. It feels like standing on the side of a choppy ocean and realising how stupid it would be to dive in even if I felt it might be a useful way to get some exercise. Clearly these are addiction metaphors and I don’t use them in a psychoanalytically naive way. I think my addiction to Twitter was worse than most people’s but social media is nonetheless suffused with addictive behaviour. From the vantage point of retreating from platforms for a couple of years and then entirely leaving them six months ago, they just look profoundly uninviting.

There’s a privilege in escaping the Twittering Machine. I have a fairly widely followed blog that’s been on the internet forever (which increasingly means it shows up in LLM responses amongst other advantages). I know how to write guest blogs for visible platforms even if I don’t do it as much as I should. I’ll be setting up a project blog and podcast imminently which I’m fairly certain someone else will be able to handle the social media for. I get invited to give lots of talks and keynotes, albeit pretty exclusively on the applied side of my work rather than the theoretical stuff I do. I’m securely employed in a place I feel valued and where people listen to me about stuff that I’m interested in. In this sense I’m not suggesting that full withdrawal from social media is a generalisable solution or even the right one for most people. But I wanted to share how I increasingly experience it, in the interests of honesty as someone who spent a big chunk of the 2010s persuading academics to use social media.

I don’t think my argument that you can use social media reflectively was wrong, only that I was naive about how platform incentives made that extremely difficult in practice. Indeed the second edition of Social Media for Academics was an attempt to work this out in real term and steer the debate in a more productive direction. Likewise I now think that my advice in Generative AI for Academics had a similar weakness in that it didn’t consider how LLMs are going to be optimised for engagement over the coming years. I slightly underplayed how difficult higher education makes it to use LLMs reflectively (though the final chapter explores this at length) but much as with social media I think the problem will soon be designed into the platforms rather than something we can circumvent through reflective practice. There are structural reasons why it’s difficult to use platforms without getting sucked into a vortex which makes attention and commitment difficult so sustain. There are certainly gains which can come through their use but everyone still using social media needs to think carefully about whether these outweigh the costs.

There’s something which clarifies when you say ‘no’ to all this. A sense of sharper edges that come from choosing boundaries rather than just letting them emerge.

#acceleratedAcademy #addiction #blog #books #life #PlatformAndAgency #platforms #promotion #selfPromotion #SocialMedia #socialMediaForAcademics #writing

The visibility of academics will be shaped through LLMs as much as social media in future

This observation by the tech journalist Casey Newton got me thinking about how LLMs are increasingly shaping the visibility of academics:

Thinking models have gotten surprisingly good at identifying potential sources — potentially academic ones. When writing about Grok last month, I wanted to talk to someone who had studied relationships between people and chatbots. ChatGPT led me to Harvard’s Center for Digital Thriving, and suggested someone to talk to, along with their email address. I wound up interviewing them for the piece. The fact that thinking models can quickly analyze the academic literature about any subject and identify prominent researchers on the subject, along with their email addresses and phone numbers, is beginning to save me a lot of Googling.

I realised early on that I was more visible in model responses (ChatGPT and Claude) than other academics of a comparable age, career stage and influence* which I assumed was because 6000 blog posts hosted on wordpress.com were gobbled up in training. It could talk at greater length, with more accuracy, about my work then it could about other academics because my online visibility translated into model visibility.

I suspect this also means I’m more prone to being suggested by the model for a topical discussion in the way that Casey points to when looking for experts to interview, though I’m unsure how to go about establishing this. The value of a long term blog also means that I figure prominently as a source for ChatGPT and software like Perplexity. Interestingly, I don’t recall ever seeing a single referral from Claude. In the last year I’ve had more referrals to this blog from ChatGPT than I have from Facebook or Bluesky, though interestingly LinkedIn drives more traffic.

In other words there’s a complex relationship between online visibility and model visibility. Given that online visibility is the key driver which led social media to be institutionalised into higher education in the UK, this is very significant for academic careers even if it takes a long time for it to consolidate into a widely recognised incentive structure.

What other factors lead to increased model visibility? Ultimately this is a matter of visibility within the training data, but the patterns of visibility produced by this are challenging to conceptualise. What are the positive and negative outcomes of increased model visibility? Casey illustrates one in terms of visibility to journalists but there are many others.

*I did this in a very impressionistic way but it would be interesting to do this as a robust quantitative exercise.

#CaseyNewton #GenerativeAIForAcademics #higherEducation #SocialMedia #socialMediaForAcademics #trainingData #visibility #wordpress

Academic networks need to prepare for waves of enshittification

After the US election in November 2024 there was a significant movement of users from Elon Musk’s X platform, which had been deployed politically by an owner now explicitly affiliated to a candidate. There’s a risk of overstating the size of the exodus, given that at the time of writing Bluesky has 30 million users compared to what clearly remains a much bigger userbase on X, even if it is difficult to trust their reported numbers given Musk’s vested interest in repudiating a narrative of decline. Even so there are now thriving communities on Bluesky engaged in patterns of interaction which are eerily reminiscent of the early years of. For many academics this has clearly been a relief following the changes imposed on Twitter/X over the last two years. Even if I remain sceptical about the future of Bluesky, for reasons I will explain below, it’s hard not to be touched by the goodwill which pervades the platform, at least if you are wired into the academic networks who are now so enthusiastically using it. 

So why did it take academics so long to leave X? In asking the question I realise that I’m interrogating my own motivations for remaining there until after the election. I found myself using the platform ever less frequently, eventually not logging on for months at a time, but I couldn’t quite bring myself to delete the account. In part this was because I was conscious that my university valued markers of public engagement, which a social media account with almost 10k followers constituted even if I rarely posted on there. It feels slightly awkward to explain that I was driven by the appearance of social capital to remain on a platform which I felt increasingly hostile to. For other academics it was the reality of the social capital which left them bound into remaining on X, even if they felt increasing uncomfortable with the culture of the platform and the user experience associated with it. If you built up a following on Twitter/X then leaving it unilaterally meant that you would lose your place within that network, missing out on the appearance and reality of visibility which can feel so significant in an anxious sector into a state of political and economic crisis.  

In my case a prominent academic blog, sites where I was a regular guest blogger and a popular Linked account meant I was less concerned about losing my connections. In fact I was in the strange position of being engaged in a slow multiyear project of shrinking my online network, having become one of the most visible sociologists on Twitter during my PhD, in support of my own wellbeing. I felt I had the platform that I wanted but I was concerned about that platform being legible to my employers in a manner they would value. Ultimately I’m not sure it matters whether it’s the connections themselves or the appearance of them which leads academics to remain committed to a social media platform. The fact our working lives are now mediated in this way is what’s really significant, such that our professional fortunes are now tied up in our use of platforms (see for example the role of the impact agenda in the UK) which once seemed like liberating spaces free of the strategic conduct which defined university life. 

This is why it’s not a simple matter for academics to move between platforms. At root these are issues posed by switching costs. What are the costs incurred when you move between platforms? To the extent a platform operates as a walled garden, a closed ecosystem controlled by a particular firm, there will be costs imposed on users who want to leave. Not only are the large platforms aware of this dynamic, they have actively built their strategy around it. For example in a recent book Cory Doctorow reflects on how the threat posed by Google’s nascent social network Google+ was perceived by Facebook, including correspondence from an executive which revealed a confident stance:   

“[P]eople who are big fans of G+ are having a hard time convincing their friends to participate because 1/there isn’t [sic] yet a meaningful differentiator from Facebook and 2/ switching costs would be high due to friend density on Facebook.”

Since Google+ ceased operating in 2019, eight years after launch, this executive’s confidence seems well founded in retrospect. This wasn’t simply a neutral observation about how the platforms had developed but rather a reflection of a deliberate policy to maximise switching costs, relying on mechanisms like photos to keep users locked into the platform. If you deliberately make it an ordeal for users to switch to another platform you fortify your own position at the cost of user experience. This reveals, as Doctorow puts it, “a company that is thoroughly uninterested in being better than its competitors – rather, they’re dedicated to ensuring that leaving Facebook behind is so punishing and unpleasant that people stay, even if they hate Facebook”. 

Bluesky is distinctive because it is built on a protocol intended to mitigate this problem. The AT Protocol describes itself as “an open, decentralized network for building social applications”. It actually emerged from a project incubated within Twitter from 2019 onwards, reflecting former CEO Jack Dorsey’s interest in a decentralised approach to social media. The problem is that, as Cory Doctorow points out, “A federatable service isn’t a federated one”. The intention to create a platform which users can leave at will, without losing their social connections, does not mean users can actually do this. It’s a technical possibility tied to an organisational promise, rather than a federated structure which enables people to move between services if they become frustrated by Bluesky. The promise to make it easy for users to exit in future is nothing more than a promise, unless there is a pathway to implementation. 

This might not feel like a problem for a platform in this early stage but we must consider where it might be heading. What happens when investors start to pressure Bluesky to increase engagement on the platform? What happens when a certain level of user growth becomes a non-negotiable condition for funding? The reason other social media platforms turned out the way they did is not due to the malign influence of bad actors (though clearly they didn’t help) but rather due to the strategic logic of building a mass commercial social media platform. If you need it to operate at scale, you design it in ways which shape user behaviour to this end, even if that wasn’t the vision which initially animated the platform. Musk pursued this logic in a particularly aggressive and politically partisan manner. In doing so he gave license to others within the digital elite to shift their public profile, as can seen in the political repositioning of Mark Zuckerberg in the last month following a longer term rebranding exercise which laid the groundwork. He did not however create the logic he was following, instead confronting an operating environment in which the uncertain economic model of the opening phase mutated into something very different, once the free trial period was over. 

The fact Bluesky has staff with patently good intention and the firm itself is a public benefit corporation doesn’t provide us with grounds to assume they will evade this trend, at least if they want to build a commercially viable business. The problem is that, as Doctorow observes, “The more effort we put into making Bluesky and Threads good, the more we tempt their managers to break their promises and never open up a federation”. If you were a venture capitalist putting many millions into Bluesky in the hope of an eventual profit, how you feel about designing the service in a way that reduces exit costs to near zero? This would mean that “An owner who makes a bad call – like removing the block function say, or opting every user into AI training – will lose a lot of users”. The developing social media landscape being tied in the Generative AI bubble means this example in particular is one we need to take extremely seriously. 

I could be wrong. It’s certainly a much better place for academics to be than Elon Musk’s X. It would be a mistake to assume it will stay that way, given the forces likely to drive enshittification. It’s illuminating to compare this (partial) academic migration to Bluesky to the failed migration to Mastodon, analysed by Wang, Koneru and Rajtmajer. While there was an “initial surge in sign-ups” following Musk’s takeover, this “did not translate into sustained long-term user engagement” because “the level of established history, as well as the strong communities established on Twitter, with some over a decade, proved too significant to overcome”. If it’s the community which holds academics in place, it raises the question of how we might better coordinate that community in future, recognising social media as the vital part of the research infrastructure which it has become. The tendency has been to see social media for academics as a trivial feature of professional life, whereas in reality it is now central to how academic networks form and reproduce. 

It can be difficult to recognise this significance because it’s far upstream from specific collaborations but the things which academics do together (empirical research, scholarly communication, public engagement etc) now frequently feature social media in their origin stories, even if not necessarily in a central role. Even though it’s become a routine feature of academic life it’s still treated as a purely individual matter, in terms of choices, training and regulation. There’s little sense of strategic purpose concerning social media as a form of digital infrastructure upon which research collaboration depends, which leaves the sector precariously outsourcing it to unpredictable private corporations. We’ve seen how badly this can work out in recent years with Twitter/X. Could we respond in a more organised and effective way to future waves of platform enshittification? I hope so but it would require universities, as well as sector-wide organisations such as funding councils and learned societies, to recognise and take a stance in relation to these issues in a way they have thus far failed to do. 

#academicNetworks #BlueSKy #coryDoctorow #elonMusk #enshittification #Mastodon #platforms #researchComms #socialMediaForAcademics #twitter #X