Could Linguistic Complexity Be Automatically Evaluated?: A Multilingual Study on WHO's Emergency Learning Platform
Samo, Giuseppe; Zhao, Yu; Guasti, Maria Teresa; Utunen, Heini; Stucke, Oliver; Gamhewage, Gaya (2022)
Samo, Giuseppe
Zhao, Yu
Guasti, Maria Teresa
Utunen, Heini
Stucke, Oliver
Gamhewage, Gaya
2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202208046221
https://urn.fi/URN:NBN:fi:tuni-202208046221
Kuvaus
Peer reviewed
Tiivistelmä
<p>The ability of assessing any type of linguistic complexity of any given contents could potentially improve knowledge reproduction, especially tacit knowledge which can be expensive during a pandemic. In this paper, we develop a simple and crosslinguistic model of complexity which considers formal accounts on the study of linguistic systems, but can be easily implemented by non-linguists' groups, e.g., communication experts and policymakers. To test our model, we conduct a study on a corpus extracted from the World Health Organization (WHO)'s emergency learning platform in 6 languages. Data extracted from open-access encyclopaedic entries act as control groups. The results show that the measurements adopted signal a trend for a minimization of complexity and can be exploited as features for (automatic) text classification.</p>
Kokoelmat
- TUNICRIS-julkaisut [24732]