Publication: Neural-network method for determining text author's sentiment to an aspect specified by the named entity
Дата
2020
Авторы
Naumov, A.
Rybka, R.
Sboev, A.
Selivanov, A.
Gryaznov, A.
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© 2020 Copyright for this paper by its authors.This study presents the approach to aspect-based sentiment analysis where a named entity of a certain category is considered as an aspect. Such task formulation is a novelty and opens up the opportunity to determine writers' attitudes to organizations and people considered in texts. This task required a dataset of Russian-language sentences where sentiment with respect to certain named entities would be labeled, which we collected using a crowdsourcing platform. Sentiment determination is based on a deep neural network with attention mechanism and ELMo language model for word vector representation. The proposed model is validated on available data on a similar task. The resulting performance (by the f1-micro metric) on the collected dataset is 0.72, which is the new state of the art for the Russian language.
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Neural-network method for determining text author's sentiment to an aspect specified by the named entity / Naumov, A. [et al.] // CEUR Workshop Proceedings. - 2020. - 2648. - P. 134-143