RusLICA: A Russian-Language Platform for Automated Linguistic Inquiry and Category Analysis
Elina Sigdel, Anastasia Panfilova
TL;DR
RusLICA presents a Python-based, LIWC-like framework tailored to Russian, constructing a 96-category analyzer from Russian semantic dictionaries, RuWordNet, RuThes, and the Russian National Corpus rather than translating English LIWC. It integrates syntactic, morphological, lexical, and statistical features via SpaCy and MyStem, plus an emotion-prediction model for LM-based classification. The system is deployed as a public web service, enabling dataset uploads, result exports, and historical tracking, with a 12-hour processing limit. The work addresses challenges of morphological richness and cultural specificity in Russian text analysis and lays groundwork for future expansion with deeper semantic parsing and broader lexical coverage. The approach aims to support researchers in psychology, linguistics, and sociolinguistics by providing a robust, language-specific tool for psycholinguistic profiling from large Russian corpora.
Abstract
Defining psycholinguistic characteristics in written texts is a task gaining increasing attention from researchers. One of the most widely used tools in the current field is Linguistic Inquiry and Word Count (LIWC) that originally was developed to analyze English texts and translated into multiple languages. Our approach offers the adaptation of LIWC methodology for the Russian language, considering its grammatical and cultural specificities. The suggested approach comprises 96 categories, integrating syntactic, morphological, lexical, general statistical features, and results of predictions obtained using pre-trained language models (LMs) for text analysis. Rather than applying direct translation to existing thesauri, we built the dictionary specifically for the Russian language based on the content from several lexicographic resources, semantic dictionaries and corpora. The paper describes the process of mapping lemmas to 42 psycholinguistic categories and the implementation of the analyzer as part of RusLICA web service.