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Record W7118968970 · doi:10.23982/vir.163133

Mitä tutkimme, kun käytämme Suomi24-korpusta?

2025· article· fi· W7118968970 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVirittäjä · 2025
Typearticle
Languagefi
FieldPsychology
TopicSemiotics and Cultural Interpretation
Canadian institutionsnot available
Fundersnot available
KeywordsData collectionContext (archaeology)Government (linguistics)Quarter (Canadian coin)

Abstract

fetched live from OpenAlex

Suomi24-foorumi on tunnettu suomalainen keskustelufoorumi, jolla käsitellään monenlaisia aiheita. Citizen Mindscapes -hankkeen vuonna 2015 julkaisemana korpusaineistona Suomi24 on ollut vilkkaassa käytössä niin yhteiskuntatieteissä kuin kielentutkimuksessa. Itse korpusta ja sen kielellisiä ominaispiirteitä ei kuitenkaan ole juuri tutkittu lingvistisestä näkökulmasta. Tämä artikkeli käsittelee Suomi24-korpusta sen edustavuuden sekä sen edustaman kielimuodon näkökulmasta. Korpusten edustavuutta voi tarkastella kahdesta näkökulmasta. Edustavuus domeenin suhteen tarkoittaa, että korpus sisältää tasapainoisen otoksen siitä kielenkäytön lajista, jota sen avulla on tarkoitus tutkia. Edustavuus distribuution mukaan tarkoittaa, että tutkittavasta kielenilmiöstä saadaan korpuksen avulla todellisuutta vastaava kuva. Suomi24-korpus on tarkoitettu ensisijaisesti hyvin suureksi laadulliseksi aineistoksi, joka ei sellaisenaan edusta mitään itseään laajempaa kokonaisuutta kuten tietokonevälitteinen viestintä tai kirjoitettu suomen kieli. Suomi24-korpuksen edustamaa kielimuotoa tarkastellaan empiirisesti kolmen tapaustutkimuksen avulla. Tapaustutkimuksissa sitä verrataan toisaalta puhuttua keskustelua edustavaan Arkisyn-korpukseen, toisaalta kirjoitettua yleiskieltä edustavaan Kansalliskirjaston sanoma- ja aikakauslehtikokoelmaan. Tapaustutkimuksissa tarkasteltavat kielenpiirteet ovat a) monikon 1. persoonan muodot (esim. me teemme – me tehdään), b) perfektitempuksen partisiipin lukukongruenssi (esim. lapset ovat syöneet – lapset on/ovat syöny) ja c) yksikön 1. ja 2. persoonan nominatiivisubjektien ilmipano (esim. teet – sä teet). Suomi24 osoittautuu tarkasteltavien piirteiden osalta varsin yleiskieliseksi. Korpuksessa on kuitenkin sisäistä variaatiota: foorumin alkuvuosien kieli on muuta aineistoa puhekielisempää, ja eri alafoorumeiden kielet eroavat toisistaan muodollisuuden asteen suhteen. Subjektin ilmipano eroaa kahdesta muusta tutkitusta piirteestä alafoorumin mukaisen distribuutionsa osalta jonkin verran. Empiirisen analyysin tulokset perustelevat tekstilajivariaation nykyistä tarkempaa huomiointia suomen kielen rakenteen ja merkityksen tutkimuksessa. What are we studying when we use the Suomi24 corpus? A corpus of online discussions as a representative of the Finnish language Suomi24 (in Finnish ‘Finland24’) is a well-known Finnish online discussion forum with sub-forums for various subjects. The Citizen Mindscapes project released the content of the forum as a corpus in 2015, and since then, it has been a popular dataset in both the social sciences and linguistics. However, the corpus itself and its linguistic properties have not been studied in depth. This article considers the Suomi24 corpus from the perspectives of representativeness and the language variety that it represents. In corpus linguistics, ensuring the representativeness of a corpus requires two kinds of considerations. Domain considerations have to do with the language variety that the corpus is supposed to represent: the corpus should be a balanced sample of the variety in question. Distribution considerations have to do with the linguistic phenomena that are studied using the corpus: the phenomenon should be distributed in the corpus in a way that resembles its distribution in the language variety as a whole. However, the Suomi24 corpus has primarily been designed as a very large qualitative dataset that is not meant to represent anything larger than itself, such as computer-mediated discourse or written Finnish. In this article, the linguistic properties of the Suomi24 corpus are examined in three case studies. In these case studies, the corpus is compared to a corpus of casual conversation (ArkiSyn) and to a corpus of standard written language (the Finnish sub-corpus of the newspaper and periodical corpus of the National Library of Finland, version 2). The case studies target morphosyntactic phenomena that are widely known to distinguish the colloquial variety of Finnish from Standard Finnish: first-person plural inflection of the verb, number agreement in perfect tense, and overt vs. non-overt subjects in first- and second-person singular subjects. The empirical analyses show that Suomi24 largely follows the conventions of Standard Finnish. However, the corpus displays internal variability: the early years of the corpus are linguistically more colloquial than the rest of the material, and different sub-forums differ from one another in terms of formality. As to the linguistic features that were analysed, the overtness of the subject seems to tap into a slightly different aspect of colloquiality from that of other features. The results support placing greater emphasis on genre variation in the study of Finnish grammar and semantics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.347
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it