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Murmansk University Develops Automatic Search Program for Neologisms and Archaisms
AIF-Murmansk reported that the Murmansk Arctic University presented an innovative project for the automatic detection of changes in language vocabulary.
To do this, we developed a special program based on a programming language that allows you to compare changes in the frequency of words in large text files. This allows you to find new and old words and track changes over time. .
— Previously, scientists searched for new words manually. That is, they could read newspaper articles, Internet forums, etc. and independently create new words from these words, which could then be analyzed and added to the dictionary. This method requires a lot of time and effort, is subjective and limited by the preferences of the scientist. Moreover, it is generally impossible to find words that come from the language in this way,” explained the author of the project, candidate of linguistic sciences, associate professor Tatyana Rychkova.
She emphasized that in general, words denoting something that does not exist, such as "caftan", or ancient Slavic words, such as "mouth", are considered useless. Our innovative project allows us to count all new and archaic words with a high level of accuracy and objectivity.
Using a special program, text files from three historical periods (pre-revolutionary from 1700 to 1916, Soviet from 1918 to 1991, and post-Soviet from 1992 to 2016) with a total volume of 250 million words were processed. Compare and analyze.
"These files will never be analyzed by humans." Even scrolling through these files is an impossible task for a human. For comparison, War and Peace has only 188,088 words," Tatyana Rychkova added.
Although this project has appeared quite recently, it has already given very interesting results. Therefore, according to the author, the number of new words greatly exceeds the number of words leaving. Despite our fears, this means that our vocabulary is becoming wider and richer. On the other hand, grammar is simplified and the number of different forms of a word or a word with the same root is reduced.
This is the first time such a study has been conducted in Russia. It is expected that based on the changes identified, it will be possible to identify general trends in vocabulary and predict future changes, for example, through the use of artificial intelligence.
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