Text complexity and abstractness: Tools for the Russian language

Abstract

The article focuses on two parallel studies aimed at validating an original automatic tool (RusAC) designed to define the level of abstractness of Russian texts. The studies were conducted on: (a) the Russian Academic Corpus (RAC) compiled of the textbooks used in middle and high schools of the Russian Federation and (b) students’ recalls of academic texts. The design of RusAC is based on the Russian Dictionary of abstractness / concreteness compiled by the authors in previous studies, which enlists abstractness ratings of over 88.000 tokens. The pilot studies pursued on the Russian Academic Corpus (circa 3 mln tokens) proved that the ratio of abstract words grows in textbooks of all disciplines across grades from 5 to 11. We also confirmed that the share of abstract words in Science textbooks is lower than that in the Humanities textbooks and that abstractness of readers’ recalls is typically lower than that of the original text as the respondents tend to omit more abstract words than concrete. The findings of the research may be applied in a wide range of spheres including education, business, PR, medicine etc. as RusAC facilitates leveling texts for different categories of readers.