new publication: examining pseudonymous academic Twitter accounts

I’m happy to report that a paper of mine (in collaboration with David E. Williams at the University of Saskatchewan) has just been published in The Internet and Higher Education. We topic modeled 77,514 tweets from 59 academically-themed but anonymous or pseudonymous Twitter accounts. This resulted in five broad topics, and we followed up with a qualitative analysis of the 100 most-representative tweets from each of those topics to generate some narrower codes. The combination of these computationally-derived topics and the human-generated codes gave us a peek into what pseudonymous academic accounts tweet about. The paper is freely available at this link through August 2nd, 2022 if you’re interested in grabbing a copy.

Based on our findings, we argued for a reframing of what ought to be considered “authentically academic” in the context of a web presence. A lot of work on academics’ online presence is based on the assumption that this has a sort of utilitarian value meant to build reputation, share research, facilitate citation, etc. In contrast, an anonymous or pseudonymous Twitter account is—by definition—incapable of providing any of this utiltarian value. However, drawing on others’ research on academics’ online presence, we argue that academics have multifaceted identities, and that the parts of an academic’s identity that are often concealed with a professional web presence can be more easily shared when one is tweeting from a pseudonym. Thus, we argue, this kind of account is just as authentic as any other academic account even if it doesn’t correspond with some of the default assumptions about why academics maintain a web presence. Here’s the abstract for another summary of the work:

Academics’ use of social media platforms is widely recognized and often understood as an extension of traditional academic practice. However, this understanding does not account for academics’ use of pseudonymous Twitter accounts. We used a combination of computational and human-driven methods to examine the activity of 59 anonymized, self-identified academics on Twitter. Our computational analysis identified five broad topics: discussing academic life, discussing British news and affairs, discussing everyday life, surviving lockdown, and engaging with academic Twitter. Within these broad topics, we identified 24 more specific codes, most of which were concentrated in individual topics, with some cross-cutting codes. These codes demonstrate how the pseudonymous accounts considered in this study can be considered “authentically academic” even if they do not conform with widespread expectations of academic social media use.

This paper took longer than I expected, but it was a delight to write, and I’m happy with the outcome. In fact, its publication this summer is a happy coincidence, since I’ve been working on leaning into my own multifaceted identity on my website and social media presence.

• macro
• Work
• research
• Twitter
• topic modeling
• qualitative research
• computational analysis
• authenticity
• Twitter research
• context collapse
• happy coincidences

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