Cross-Regional Sentiment Analysis of VKontakte Communities: Typical Krasnodar vs. Typical Kemerovo

Author:

Ryabchenko Natal'ya1,Malysheva Ol'ga1

Affiliation:

1. Kuban State University

Abstract

This research tested a complex analytical method based on semantic modeling of discursive fields and network analysis that can be applied to networked linguistic data. The copyright software package Monitoring and Analysis of Social Networks, Internet Communities, and Users provided automatic data processing to restore the semantic core of the discursive fields generated by Typical Krasnodar and Typical Kemerovo online communities in 2021–2022. The analysis was visualized as social graphs and semantic core models. It identified a number of sensitive topics that generated a lot of feedback. The method also proved efficient in predicting cultural and socio-political trends. The complex methodology provided rapid identification of amplified discursive activity, conditions for social unrest, and bifurcation points for destructive social practices. The results may contribute to effective information management and social strain relief in the regions through discursive control of online communication.

Publisher

Kemerovo State University

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