Regiolect lexicography: Problems and their solutions in the age of digitalization

The article examines the development and transition from traditional dialect lexicography to regiolect studies. The authors consistently reveal the formation of regiolectography, demonstrate the evolution of the term "regio-lect", analyze and compare current regiolectographic trends in Russian, European, and American lexicography. The article offers a broad overview of currently available poly- and mono-regiolect dictionaries, the material of which is usually drawn from a clearly defined territorial area and is limited mainly to the boundaries of one city, less often a region. Based on the analysis of lexicographic sources, as well as their own lexicographic experience, the authors establish two levels of difficulties in regiolect lexicography. Problematic aspects of the microlevel are associated with lexicographic parameterization, description and subsequent design of the dictionary and its entries. At this level, the dilemmas of dictionary content are considered: placement in one dictionary of regional appellatives, toponyms and microtoponyms, andtheir referential and conceptual meanings. The solution to these microlevel questions cannot be unambiguous since it depends both on lexicographers and on the concept of the dictionary being compiled and the available regional material. The problems of macrolevel regiolect lexicography are determined by the creation of a lexicographic database (at the methodological, procedural and source fields). At this level, the most labor-intensive tasks of lexicographers are: searching for and compiling a database of regiolect lexemes, establishing their motivational bases, selecting illustrations of the meaning and features of the use of units of interest. These lexicographic processes can be facilitated, accelerated or even fully implemented thanks to their digitalization. As an example, a case study of a project to compile a regiolect dictionary of the Arkhangelsk city is given. In the work on the dictionary, the authors choose the big data technology as leading method. More than half a million of texts and comments to them from 46 regional social media, as well as the results of remote automated surveys of informants serve as source of data. Search, collection, aggregation and analysis of lexemes-candidates for the dictionary and illustrative examples are carried out in a specially created multifunctional web application, which also allows statistical and geolocation data processing. Digitalization of lexicographic processes helps to correct semantics, clarify grammar and stylistic affiliation of regional lexemes, and identify their connotations. The prospect of such work may be dictionary atlases of cities, subsequently united into a single large network in digital format. The authors declare no conflicts of interests.

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