Kirill Maslinsky
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maslinych.bsky.social
Kirill Maslinsky
@maslinych.bsky.social
Computational literary studies with a modicum of pure linguistics | research design, infrastructure and methods guy | open data enthusiast and curator | doing theory+engineering @ ERC Advanced project “Theory of tone” @ INALCO, Paris
As a gift for a patient reader, a graph showing the cohorts in terms of total print runs. *Graphs are better news
March 26, 2025 at 5:48 AM
no context graph: the number of translated books for children printed in Soviet Russia and USSR 1918-1984, split into “cohorts” by the moment a translated author first appears in the data. In red are mostly those “classics” who stay with us: Grimms, Andersen, Jules Verne etc.
March 26, 2025 at 5:48 AM
The data is part of Daria's ongoing research, and she does wonderful things with it. As a teaser, here's Daria's graph showing cosine similarity between journals based on the poets who published there. Huge shoutout to Daria for sharing these data!
March 3, 2025 at 4:09 PM
How many tonal languages are out there in the world? If you need an estimate based on most comprehensive database to date, here it is: 42.7%. Concisely on a poster presented today at the #OCP22 conference in Amsterdam: zenodo.org/records/1481.... The database itself is online and has more ↓
February 5, 2025 at 8:37 PM
No context graph: a yearly proportion of total print run of all books for children printed in Soviet Russia/USSR split by gender of the author. Note the fluctuations of the share of the female authors. 1931 marks the governmental ban of private publishers, 1941 the nazi invasion. →
December 27, 2024 at 7:51 PM
Results: Death of the autocrat Nicolas I mattered, censorship pressure went down indeed. New editorial team was more politically-minded, it mattered too. But we don't see the expected resumption of censorship in the corpus. Authorities just closed the magazine. 8/n
November 30, 2024 at 4:12 PM
To properly account for the uncertainty and document-level confounders we define document-level topic dissociation as a probability to see one of the topics in it, but not both. We estimated dissociation with Bayesian generalized linear model. dT is topic dissociation, T1,T2 - topics. 7/n
November 30, 2024 at 4:12 PM
We measure topics with LDA, and censorship pressure with topical dissociation. Dissociation happens when one or the other of two topic (either literature or politics) occur in a document, but not both (a shaded area on the graph). 6/n
November 30, 2024 at 4:12 PM
Changes in the political and censorship regime shaped our expectations of the level of censorship pressure. Higher point on a graph mean higher pressure. The editorial team also changed, and article length varied. All this affects topic distribution and should be taken into account. 5/n
November 30, 2024 at 4:12 PM
Can we see censorship in a historical corpus when it's hidden in plain sight? Our new #CHR2024 paper with Ekaterina Vozhik and @romanlisiukov.bsky.social looks for the footprint of censorship pressure in the trends of topic co-occurrence. 1/n
November 30, 2024 at 4:12 PM