Extracting sentiments towards COVID-19 aspects

ABSTRACT

In this paper, we introduce a specialized Russian dataset and study approaches for aspect-based sentiment analysis of Russian users’ comments about the COVID-19. We solve two tasks, namely Relevance Determination (RD), which aims to predict whether a sentence is relevant to an aspect of the pandemic, and Sentiment Classification (SC), which classifies the sentiment expressed towards an aspect in a sentence. We applied and tested various methods of machine learning, including finetuning of the pre-trained RuBERT model. The best results in both tasks were obtained by RuBERT model in the Natural Language Inference (NLI) formulation. Copyright © 2021 for this paper by its authors.