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World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
World Applied Sciences Journal. Т. 32, №7. С. 1455-1459. Is Sentiment Analysis Domain-Dependent?
Neo-sentimentalism of L.S. Petrushevskaya in the light of catharsis through laughter and tears
Kubasov, A. V.
this story as sentimental naturalism. However, the movie script by Petrushevskaya, based on the story
Numerical Study of the Consensus Degree Between Social Network Users in the Group Decision Making Process
Chukhno O., Chukhno N., Gaidamaka A., Samouylov K., Herrera-Viedma E.
operate with exact numbers. Experts are required to provide estimates in terms of qualitative aspects
Mapping Texts to Multidimensional Emotional Space: Challenges for Dataset Acquisition in Sentiment Analysis
Alexander, Kalinin, Anastasia, Kolmogorova, Galina, Nikolaeva, Alina, Malikova
The cornerstone for any sentiment analysis research is labeled data and its acquisition. Canonical
Mapping Texts to Multidimensional Emotional Space: Challenges for Dataset Acquisition in Sentiment Analysis
Alexander, Kalinin, Anastasia, Kolmogorova, Galina, Nikolaeva, Alina, Malikova
The cornerstone for any sentiment analysis research is labeled data and its acquisition. Canonical
Analysis of 19.9 million publications from the PubMed/MEDLINE database using artificial intelligence methods: Approaches to the generalizations of accumulated data and the phenomenon of “fake news” [Анализ 19,9 млн публикаций базы данных PubMed/MEDLINE методами искусственного интеллекта: подходы к обобщению накопленных данных и феномен “fake news”]
Yu T.I., Gromova O.A., Stakhovskaya L.V., Vanchakova N.P., Galustyan A.N., Kobalava Zh.D., Grishina T.R., Gromov A.N., Ilovaiskaya I.A., Kodentsova V.M., Kalacheva A.G., Limanova O.A., Maksimov V.A., Malyavskaya S.I., Mozgovaya E.V., Tapilskaya N.I., Rudakov K.V., Semenov V.A.
of a system for sentiment analysis (i.e. analysis of emotional modality) of biomedical publications
An automatic procedure to create fuzzy ontologies from users’ opinions using sentiment analysis procedures and multi-granular fuzzy linguistic modelling methods
Morente-Molinera J.A., Kou G., Pang C., Cabrerizo F.J., Herrera-Viedma E.
that can be easily accessed and processed. In this paper, a novel method that uses sentiment analysis

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