Oleg Sobchuk 🇺🇦
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sobchuk.bsky.social
Oleg Sobchuk 🇺🇦
@sobchuk.bsky.social
1.7K followers 870 following 560 posts
I use big data to research the cultural evolution of arts @ Max Planck Institute for Evolutionary Anthropology
More: https://www.sobch.uk/
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sobchuk.bsky.social
Oleg Sobchuk 🇺🇦 @sobchuk.bsky.social · Feb 5
Change over time is often depicted as a trendline. But what does shape a trendline? Which forces? Our new paper presents a method allowing to “decompose” trendlines into constituent forces. Also, we tackle an old puzzle: Does culture change “one funeral at a time”? 🧵(1/8) doi.org/10.1098/rspb...
a schematic depiction of a trend line and several causal forces that give it its shape
sobchuk.bsky.social
Before the monstrous transformation of Twitter to X, it was considered normal to be active on academic Twitter. Now, even though we've migrated to Bluesky ("safe space"), I feel that many ppl (including myself) are less active in posting anything. Have you noticed this trend? Or am I imagining this?
November 25, 2025 at 12:20 PM
Reposted by Oleg Sobchuk 🇺🇦
jbgruber.bsky.social
After a long time in development, {traktok} #rstats is now finally on CRAN!

Whether you have access to the Research API or just want to scrape some pages, traktok has you covered

jbgruber.github.io/traktok/
November 24, 2025 at 8:50 PM
Reposted by Oleg Sobchuk 🇺🇦
artjomshl.bsky.social
it's interesting to project the chatgpt's style into the past -- read historical texts with an LLM detector.

What are its precursors? What are the linguistic registers on which it depends?

Back-cover publisher texts seems like one good candidate to me
a text screenshot from Damrosch's What is World Literature (2003), highlighted text quotes back-cover copy of Modern Literature of the Non-Western World (1995): "Travel to 61 countries and experience a vast selection of poetry, fiction, drama, and memoirs...make stops in Asia, Southeast Asia, the Middle East, Africa, Latin America, and the Caribbean. . . . Your passport? Modern Literature of the Non-Western World"
November 24, 2025 at 5:10 PM
sobchuk.bsky.social
📚 MajinBook: an impressive new dataset by Antoine Mazières & @tpoibeau.bsky.social. Metadata for 500,000 books from Library Genesis & GoodReads. Mostly books from the last 100 years or so, see the plot ⬇️ arxiv.org/abs/2511.11412
Temporal distribution of books in the corpus
November 21, 2025 at 5:24 PM
Reposted by Oleg Sobchuk 🇺🇦
jbarre.bsky.social
What happens when we model the detective archetype at scale? 🕵️‍♂️📚
Our new paper, accepted for #CHR2025 combines literary history and computational modeling to trace how the figure of the detective evolves across 150 years of French fiction.

arxiv.org/pdf/2511.00627
November 4, 2025 at 5:36 PM
Reposted by Oleg Sobchuk 🇺🇦
ibogost.com
I have just discovered that Apple brought back the C/AC button in the calculator app in iOS 26, an act I take full credit for.
A Calculator’s Most Important Button Has Been Removed
This is clearly a mistake.
www.theatlantic.com
October 22, 2025 at 8:30 PM
Reposted by Oleg Sobchuk 🇺🇦
artjomshl.bsky.social
A reminder that we are accepting submissions for a themed issue at Computational Humanities Research journal 📙

Deadline is end of February 2026!
artjomshl.bsky.social Artjoms Šeļa @artjomshl.bsky.social · Jul 4
⚡ CFP: a themed issue in Computational Humanities Research!

Meaning, Form, and History in Computational Poetics: if you work on all things verse, all things form, in any language, consider submitting!

for questions reach out to me or @nmhouston.bsky.social !

www.cambridge.org/core/journal...
Call for Papers @ CHR: Meaning, Form, and History in Computational Poetics
October 14, 2025 at 2:43 PM
Reposted by Oleg Sobchuk 🇺🇦
bjornlindstrom.bsky.social
How do humans keep inventing tools and technologies that no single person could create alone?

Our new preprint, led by
@anilyaman.bsky.social & @ts-brain.bsky.social
shows that semantic knowledge guides innovation and drives cultural evolution. 🧠📘 arxiv.org/abs/2510.12837
October 16, 2025 at 1:49 PM
sobchuk.bsky.social
Joel Mokyr received a Nobel! It's a wonderful signal for cultural evolution scholars. Mokyr was defending an evolutionary approach to economic history for 40 years. Check out A Culture of Growth, The Gifts of Athena, or The Lever of Riches: some of the books that inspired me the most. I interpret...
nytimes.com The New York Times @nytimes.com · Oct 13
Breaking News: The Nobel Memorial Prize in Economics was awarded to Joel Mokyr, Philippe Aghion and Peter Howitt for their work on how technology drives growth.
Three Share Nobel in Economics for Work on How Technology Drives Growth
Joel Mokyr was awarded half of the prize, and Philippe Aghion and Peter Howitt shared the other half.
nyti.ms
October 13, 2025 at 1:59 PM
Reposted by Oleg Sobchuk 🇺🇦
incertaesedis.bsky.social
Happy to share our new paper introducing the Animal Culture Database in Scientific Data: We’re putting together a resource consolidating primary research on cultural behaviors in wild animal populations and how they’re affected by human activity (1/5) www.nature.com/articles/s41...
Mapping nonhuman cultures with the Animal Culture Database - Scientific Data
Scientific Data - Mapping nonhuman cultures with the Animal Culture Database
www.nature.com
June 22, 2025 at 11:16 PM
Reposted by Oleg Sobchuk 🇺🇦
fusaroli.bsky.social
Why does Western Paleolithic cave art strongly prefer animal side views and often use abbreviations? Our new paper in Topics in Cognitive Science challenges long-held assumptions about these artistic choices using cognitive science experiments. A thread 1/n
onlinelibrary.wiley.com/doi/10.1111/...
September 15, 2025 at 2:41 PM
Reposted by Oleg Sobchuk 🇺🇦
dbamman.bsky.social
The UC Berkeley School of Information is hiring an assistant professor in the broad field of Information--including areas of info seeking/retrieval, digital humanities, cultural analytics, info viz, & philosophy of information (among others). Deadline Nov 1! aprecruit.berkeley.edu/JPF05014
Assistant Professor - Information - School of Information
University of California, Berkeley is hiring. Apply now!
aprecruit.berkeley.edu
September 23, 2025 at 2:43 PM
Reposted by Oleg Sobchuk 🇺🇦
danielnettle.bsky.social
Delighted to announce the publication of 'From Questions to Knowledge', my new and updated statistics and data analysis handbook.
www.danielnettle.eu/2025/09/14/f...
From Questions to Knowledge
I am delighted to announce the publications of my statistics and data analysis book, ‘From Questions to Knowledge: Data Analysis for Psychology and Behavioural Science Using R’.  This b…
www.danielnettle.eu
September 14, 2025 at 5:41 PM
sobchuk.bsky.social
Cool new paper (and a thread about it) by @babeheim.bsky.social on the cultural evolution of Go games! Check out these colourful decision trees 🔥 doi.org/10.1017/ehs....
September 16, 2025 at 3:02 PM
Reposted by Oleg Sobchuk 🇺🇦
joachimbaumann.bsky.social
🚨 New paper alert 🚨 Using LLMs as data annotators, you can produce any scientific result you want. We call this **LLM Hacking**.

Paper: arxiv.org/pdf/2509.08825
We present our new preprint titled "Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation". We quantify LLM hacking risk through systematic replication of 37 diverse computational social science annotation tasks. For these tasks, we use a combined set of 2,361 realistic hypotheses that researchers might test using these annotations. Then, we collect 13 million LLM annotations across plausible LLM configurations. These annotations feed into 1.4 million regressions testing the hypotheses. For a hypothesis with no true effect (ground truth $p > 0.05$), different LLM configurations yield conflicting conclusions. Checkmarks indicate correct statistical conclusions matching ground truth; crosses indicate LLM hacking -- incorrect conclusions due to annotation errors. Across all experiments, LLM hacking occurs in 31-50\% of cases even with highly capable models. Since minor configuration changes can flip scientific conclusions, from correct to incorrect, LLM hacking can be exploited to present anything as statistically significant.
September 12, 2025 at 10:33 AM
sobchuk.bsky.social
My copy of the Oxford Handbook of Cultural Evolution has arrived! Looks gorgeous – and massive. And somewhere on page 554 (which is roughly the middle of the book 😅) you can find my chapter.

Big thanks to the editors for organizing this!
Front cover of the Oxford Handbook of Cultural Evolution The chapter "Evolution of Modern Literature and Film" in this volume
September 15, 2025 at 3:18 PM
Reposted by Oleg Sobchuk 🇺🇦
carlbergstrom.com
1. What does a Cold War-era game theory problem known as the silent duel have to do with high-risk research strategies, publication in Cell/Nature/Science glamor journals, and the academic job market?

Kevin Gross and I tackle these questions in our latest arXiv preprint: arxiv.org/abs/2509.06718
How competition propels scientific risk-taking Kevin Gross∗ Department of Statistics North Carolina State University Raleigh, NC USA Carl T. Bergstrom† Department of Biology University of Washington Seattle, WA USA (Dated: September 9, 2025) In science as elsewhere, attention is a limited resource and scientists compete with one another to produce the most exciting, novel and impactful results. We develop a game-theoretic model to explore how such competition influences the degree of risk that scientists are willing to embrace in their research endeavors. We find that competition for scarce resources—for example, publications in elite journals, prestigious prizes, and faculty jobs—motivates scientific risk-taking and may be important in counterbalancing other incentives that favor cautious, incremental science. Even small amounts of competition induce substantial risk-taking. Moreover, we find that in an “opt-in” contest, increasing the stakes induces increased participation—which crowds the contest and further impels entrants to pursue higher-risk, higher-return investigations. The model also illuminates a source of tension in academic training and collaboration. Researchers at different career stages differ in their need to amass accomplishments that distinguish them from their peers, and therefore may not agree on what degree of risk to accept.
September 14, 2025 at 1:50 PM
Reposted by Oleg Sobchuk 🇺🇦
culturalevolsoc.bsky.social
The count down starts for #CESRabat! Follow @ces2026.bsky.social and join us May 11-13 next year for an exciting meeting in Rabat, Morocco.

Massive thanks to the #CESRabat organising committee:
Sarah Alami (co-chair)
Mathieu Charbonneau (co-chair)
Zachary Garfield
Edmond Seabright
September 13, 2025 at 3:14 AM
sobchuk.bsky.social
"Is it getting harder to make a hit?" – asks this new paper. Short answer: yes.

"The inequality in song lifetimes has increased rapidly since the turn of the millennium. Top-10 songs are lingering on the chart for longer and longer"

epjdatascience.springeropen.com/articles/10....
Is it getting harder to make a hit? Evidence from 65 years of US music chart history - EPJ Data Science
Since the creation of the Billboard Hot 100 music chart in 1958, the chart has been a window into the music consumption of Americans. Since its introduction, the chart has documented music consumption...
epjdatascience.springeropen.com
September 11, 2025 at 3:13 PM
Reposted by Oleg Sobchuk 🇺🇦
mpi-nl.bsky.social
For decades, linguists assumed kids drive language change through ‘imperfect’ learning. New research by Raviv, Blasi & Kempe (Psychological Review) show that instead, adolescents and young adults are more likely to spread, normalize, and cement linguistic shifts. www.mpi.nl/news/young-c...
September 9, 2025 at 10:45 AM
sobchuk.bsky.social
Great news from the @erc.europa.eu today: I received an ERC Starting Grant to study the cultural evolution of literature 🔥

www.eva.mpg.de/press/news/a...
Charting the evolution of European literature
Oleg Sobchuk has received an ERC Starting Grant to study 200 years of European literary evolution
www.eva.mpg.de
September 4, 2025 at 11:45 AM
Reposted by Oleg Sobchuk 🇺🇦
rmcelreath.bsky.social
Humans are in fact a venomous species (Figure 6 from "A global database on blowguns with links to geography and language" Aguirre-Fernández et al doi.org/10.1017/ehs....)
Figure 6. Map showing projectile types and the use of toxins in the world sample (a). Grey points represent unavailable data. Poison is only used in association with darts within this data set (not in pellets). The term ‘darts’ does not exclude an association with the use of poison, but may rather reflect a lack of information. The eastern USA is generally believed to use darts without toxins, but this has never been systematically studied and is therefore regarded as ambiguous. Our results show that some North American groups are reported to use toxins. The two ‘hotspots’ for blowguns are located in South East Asia (b) and South America (c). Darts are much more prevalent than pellets and pellets are more strongly associated with the ‘single’ type (d).
August 29, 2025 at 12:55 PM
Reposted by Oleg Sobchuk 🇺🇦
kyleflaw.com
🪦 New in @pnas.org: we analyzed 38 million U.S. obituaries to ask what signals a life well lived:

What values are people most remembered for?

How do legacies shift with cultural events?

How do age and gender shape what it means to have lived well?

www.pnas.org/doi/10.1073/...
An exploration of basic human values in 38 million obituaries over 30 years | PNAS
How societies remember the dead can reveal what people value in life. We analyzed 38 million obituaries from the United States to examine how perso...
www.pnas.org
August 27, 2025 at 2:39 AM
Reposted by Oleg Sobchuk 🇺🇦
dingdingpeng.the100.ci
Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...
Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities Abstract Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models). Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve. A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals). Illustrated are 1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals 2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and 3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.
August 25, 2025 at 11:49 AM
sobchuk.bsky.social
I happened to accidentally find this edited volume on quantitative approaches to literature, from 1969. Never heard of it - even though it was co-edited by one of the big figures in narratology: Lubomir Doležel (another surprise). The minimalist plots here are ⚡️
August 25, 2025 at 1:23 PM