Development of the automatic system based on the three-factor communication model for the extraction and classification of the comments in social media
The paper aims at examining the main communication strategies used by those involved into risk communication on the governmental regulations on the management of the adverse aftermaths of the crises (on the case of COVID-19 pandemics). In order to extract and classify the set of comments, a three-factor model was developed to classify the texts and comments through S. Hall’s 'encoding/decoding' model, N. Luhmann’s functional subsystems theory, and communicational strategies' types. Using tools for the automatized data extraction we got the texts (76.000) and comments (1.500.000) samples and developed a neural network classifying the texts decoding regimes during its interpretation. The approach developed by authors both allows to consider the issues, and the 'measures/statements — reactions' model, it helps to examine broader set of governmental measures and statements, users' reactions and analyze texts in the Russian language.