Melanie Walsh
@mellymeldubs.bsky.social
3.8K followers 780 following 420 posts
Asst Prof @ University of Washington Information School // PhD in English from WashU in St. Louis I’m interested in books, data, social media, and digital humanities. They call me "Eyre Jordan" on the bball court 🏀 https://melaniewalsh.org/
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mellymeldubs.bsky.social
I made a lil game inspired by the Wordle universe. It's called Versedle (pronounced Verse-a-dle). You guess who wrote famous lines of literature.

As my parents can attest, it's hard! I made them an Easy Mode, but it's still kinda hard. Maybe you'll like it!

▶️ 📚: melaniewalsh.github.io/versedle/
VERSEDLE
Test your literary knowledge with Versedle!
melaniewalsh.github.io
mellymeldubs.bsky.social
Autofiction is good.
rachelfeder.bsky.social
Tell me your most unhinged literary opinion, as a little treat
Reposted by Melanie Walsh
rachelfeder.bsky.social
Tell me your most unhinged literary opinion, as a little treat
Reposted by Melanie Walsh
mmvty.bsky.social
📣 New preprint! We know humans are biased against AI-creativity. But what about LLMs, now often judging creativity in various contexts? Do they replicate, transform, or amplify this bias? We tested it. Turns out: AI is 2.5X more biased against its own work than humans. arxiv.org/pdf/2510.08831 🧵
arxiv.org
Reposted by Melanie Walsh
heuser.bsky.social
As in work by @mellymeldubs.bsky.social et al, I examine formal tendencies in the poetic output of 9 LLMs. I find that LLM verse is "formally stuck" on rhyme & regular meter, producing these forms far more than even the formally strictest periods of literary history—and even when instructed not to.
Figure 1.Frequency of rhymed poems in the Chadwyck-Healey corpora compared with LLM-generated verse. Generative models were prompted for three types of poems: rhyming poems, unrhyming poems, and poems without specifying whether to rhyme. Points indicate mean likelihood; size indicates the number of poems per data point; whiskers show standard error.

The left-hand portion of the graph shows that historically, across the 1,000 sampled poems per half-century in the Chadwyck-Healey poetry collections, the average likelihood for a poem to rhyme descends over time, particularly since the late nineteenth century. Prior to that, the historical incidence of rhymed verse hovers between 71% and 90% for three centuries, before turning away from it in the late nineteenth century (71%) and plummeting in the early twentieth (15%)—with ultimately only 7% of poems written by postwar poets in rhyme.

Meanwhile, the right-hand portion of the graph, a distant reading of rhyme not in historical but generative verse, shows several striking findings. On average across the LLMs, prompts for a rhyming poem (shown in blue) and prompts simply for a poem without specifying whether to rhyme (shown in green) produce a body of artificial verse composed of 95% rhyming poetry. Not only is this incidence more than in any historical period of actual human-authored verse, but its similarity across these two categories of prompts suggests a remarkably stubborn association between the genre of poetry and the form of rhyme within these models. Furthermore, whether prompted simply to write a poem, a rhyming poem, or an unrhyming poem (shown in purple), generative models—despite the overwhelming bias in their training data toward the contemporary—rhyme more often than poets born in the late twentieth century, and sometimes significantly more. Finally, even prompting the models for an unrhyming poem yields rhyming poems 50% of the time on average across the models, more than seven times as often as in the … Figure 6.Frequency of syllable stress per syllable position into 10-syllable lines, drawn from historical and generative sonnets. Points indicate mean likelihood; whiskers indicate standard error.

Even before attempting to metrically scan these syllable stresses, Figure 6 shows how generative sonnets arrange their unstressed and stressed syllables more regularly than in any known century of the form. That LLM imitations of Shakespeare’s sonnets (in red) dip much lower in syllable stress likelihood in the odd-numbered syllables and peak much higher in the even-numbered ones—more than any other sonnet source, including Shakespeare’s own—shows how inhumanly rigidly its syllable stresses adhere to an iambic pentameter metrical template. The second syllable in the line, for example, is stressed 62% of the time in twentieth-century sonnets; 63% Shakespeare; and 69% in pre-twentieth-century sonnets, partly given the more frequent use of traditional metrical variations like the trochaic inversion. But LLM verse stresses this syllable a striking 89% of the time, far exceeding the sonnets of any historical period from the seventeenth through the twentieth centuries. Although this syllable shows the largest difference between generative and historical sonnet meter, and although all sonnet sources rise in regularity toward the end of the line (a well-known phenomenon in metrics), generative sonnets maintain an historically unprecedented regularity in syllable stress across the line.
Reposted by Melanie Walsh
heuser.bsky.social
Excited to share my latest publication, "Generative Aesthetics: On formal stuckness in AI verse." It's published in a special issue in the Journal of Cultural Analytics, expertly edited by Tess McNulty and Laura Chapot, on "Computation and Form, Reconsidered."
culturalanalytics.org/article/1448...
Generative Aesthetics: On formal stuckness in AI verse | Published in Journal of Cultural Analytics
By Ryan Heuser. This paper examines the formal and aesthetic patterns of AI-generated poems through a series of computational experiments.
culturalanalytics.org
Reposted by Melanie Walsh
sjjphd.bsky.social
Curious if folks are getting the impression that those around them are unaware antifa is not an org? We know this admin is dead set on pretending it is & many media are uncritically perpetuating that. Feels like we’re watching an elite disinfo campaign move in both a rapid and absurdist fashion.
karlbode.com
you'd think a prominent news outlet like the New York Times might mention that "antifa" isn't an actual organization in a long story about antifa, but nope!

and the subhead helps props up a false claim this professor was up to something seedy as something up for debate
NYT headline: "Rutgers Expert on Antifa Tries to Flee to Spain After Death Threats"

subheadline: "Mark Bray was teaching courses on antifascism. Turning Point USA accused him of belonging to antifa, which he denies. His flight to Spain was canceled abruptly on Wednesday night."
Reposted by Melanie Walsh
Reposted by Melanie Walsh
rafaelwalker.bsky.social
Happy to announce that both my departments—English and Black & Latino Studies (BLS)—are hiring for TT positions this year!

In English, we're hiring in Anglophone South Asian.
cuny.jobs/new-york-ny/...
Jobs | City University of New York
cuny.jobs
mellymeldubs.bsky.social
Baker & Taylor had pivoted toward algorithmic and digital tools in recent years. In 2011, they acquired (the parent company of) CollectionHQ, a management software widely used by libraries, which includes algorithms that predict how well books will circulate and automated diversity audit tools.
mellymeldubs.bsky.social
Wow I can't believe that Baker & Taylor is going under. Fully agree that book distribution is a huge and often overlooked part of publishing and libraries.

We wrote a bit about B&T's history and relationship to public libraries in our recent FAccT paper: dl.acm.org/doi/full/10....
sarahweinman.com
Distribution is THE under-reported story in book publishing (outside of the trade publications) and losing B&T is going to have untold ripple effects on the industry, small presses, and authors.
Reposted by Melanie Walsh
Reposted by Melanie Walsh
heatherfro.bsky.social
We talked about how I made this workshop on Thursday; today (Tuesday) at 2pm in the University of Arizona Main Library Data Studio we're doing it live & in person! my slides are here if you want to have a look www.dropbox.com/scl/fi/pwo8s..., huge hat tip to @mellymeldubs.bsky.social
Reposted by Melanie Walsh
chanda.blacksky.app
🚨🚨 My dear friend and fellow academic, the Palestinian American sociologist @emanabdelhadi.bsky.social has been taken by the Cook County Sheriff near Chicago. They have not mirandized her. Please signal boost. All eyes on Broadview for Eman and the community she was defending 🚨🚨
mellymeldubs.bsky.social
Haha but you got it! Even when you know the poem, it's sometimes disorienting in this form!
mellymeldubs.bsky.social
I'm sorry, and you're welcome 😅
mellymeldubs.bsky.social
Yay glad you think it's fun! 💓
Reposted by Melanie Walsh
wwilloww.bsky.social
Thank you, @mellymeldubs.bsky.social What fun!
mellymeldubs.bsky.social
I made a lil game inspired by the Wordle universe. It's called Versedle (pronounced Verse-a-dle). You guess who wrote famous lines of literature.

As my parents can attest, it's hard! I made them an Easy Mode, but it's still kinda hard. Maybe you'll like it!

▶️ 📚: melaniewalsh.github.io/versedle/
VERSEDLE
Test your literary knowledge with Versedle!
melaniewalsh.github.io
Reposted by Melanie Walsh
molly.wiki
New research from AWU/CWU/Techquity on AI data workers in North America. “[L]ow paid people who are not even treated as humans [are] making the 1 billion dollar, trillion dollar AI systems that are supposed to lead our entire society and civilization into the future.”
cwa-union.org/ghost-worker...
We identify four broad themes that should concern policymakers: Workers struggle to make ends meet. 86% of surveyed workers worry about meeting their financial responsibilities, and 25% of respondents rely on public assistance, primarily food assistance and Medicaid. Nearly two-thirds of respondents (66%) report spending at least three hours weekly sitting at their computers waiting for tasks to be available, and 26% report spending more than eight hours waiting for tasks. Only 30% of respondents reported that they are paid for the time when no tasks are available. Workers reported a median hourly wage of $15 and a median workweek of 29 hours of paid time, which equates to annual earnings of $22,620. Workers perform critical, skilled work but are increasingly hamstrung by lack of control over the work process, which results in lower work output and, in turn, higher-risk AI systems. More than half of the workers who are assigned an average estimated time (AET) to complete a task felt that AETs are often not long enough to complete the task accurately. 87% of respondents report they are regularly assigned tasks for which they are not adequately trained. With limited or no access to mental health benefits, workers are unable to safeguard themselves even as they act as a first line of defense, protecting millions of people from harmful content and imperfect AI systems. Only 23% of surveyed workers are covered by health insurance from their employer. Deeply involved in every aspect of building AI systems, workers recognize the wide range of risks that these systems pose to themselves and to society at large. Fifty-two percent of surveyed workers believe they are training AI to replace other workers’ jobs, and 36% believe they are training AI to replace their own jobs. 74% were concerned about AI’s contribution to the spread of disinformation, 54% concerned about surveillance, and 47% concerned about the use of AI to suppress free speech, among other issues.
mellymeldubs.bsky.social
Pay WNBA players what you owe them!

All-star WNBA rookies make like $70k while their NBA counterparts make like $12 million... umm that's crazy.

The league is booming, and the players deserve their share. Keep up the pressure!

www.nytimes.com/athletic/667...
WNBA players say CBA negotiations are stalling as deadline nears
www.nytimes.com