Publication:
Neural-network method for determining text author's sentiment to an aspect specified by the named entity

dc.contributor.authorNaumov, A.
dc.contributor.authorRybka, R.
dc.contributor.authorSboev, A.
dc.contributor.authorSelivanov, A.
dc.contributor.authorGryaznov, A.
dc.contributor.authorРыбка, Роман Борисович
dc.contributor.authorСбоев, Александр Георгиевич
dc.date.accessioned2024-11-27T08:25:49Z
dc.date.available2024-11-27T08:25:49Z
dc.date.issued2020
dc.description.abstract© 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.
dc.format.extentС. 134-143
dc.identifier.citationNeural-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
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85092329377&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/22431
dc.relation.ispartofCEUR Workshop Proceedings
dc.titleNeural-network method for determining text author's sentiment to an aspect specified by the named entity
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume2648
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