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RuBERT Embeddings in the Task of Classifying User Posts on a Social Media. / Oliseenko, Valerii D.; Abramov, Maxim V.

Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022: Proceedings. ed. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2022. p. 31-33.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Oliseenko, VD & Abramov, MV 2022, RuBERT Embeddings in the Task of Classifying User Posts on a Social Media. in S Shaposhnikov (ed.), Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022: Proceedings. Institute of Electrical and Electronics Engineers Inc., pp. 31-33, 25th International Conference on Soft Computing and Measurements, SCM 2022, St. Petersburg, Russian Federation, 25/05/22. https://doi.org/10.1109/scm55405.2022.9794844

APA

Oliseenko, V. D., & Abramov, M. V. (2022). RuBERT Embeddings in the Task of Classifying User Posts on a Social Media. In S. Shaposhnikov (Ed.), Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022: Proceedings (pp. 31-33). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/scm55405.2022.9794844

Vancouver

Oliseenko VD, Abramov MV. RuBERT Embeddings in the Task of Classifying User Posts on a Social Media. In Shaposhnikov S, editor, Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022: Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. p. 31-33 https://doi.org/10.1109/scm55405.2022.9794844

Author

Oliseenko, Valerii D. ; Abramov, Maxim V. / RuBERT Embeddings in the Task of Classifying User Posts on a Social Media. Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022: Proceedings. editor / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 31-33

BibTeX

@inproceedings{6c8a3586d00849f3b5ac131d38578aef,
title = "RuBERT Embeddings in the Task of Classifying User Posts on a Social Media",
abstract = "This paper presents models for solving the problem of multiclass classification of user posts in a social media. These models are based on embeddings extracted from messages using the RuBert language model and a fully connected neural network built over it. The models presented are compared to a baseline model using long-Term short-Term memory neurons (LSTM). The results will improve the accuracy of the classification posts, which in turn will improve the accuracy of assessing the psychological characteristics users. ",
keywords = "analysis of social media posts, fully connected neural network, LSTM, machine learning, multi-class classification, RuBert, sentence embedding",
author = "Oliseenko, {Valerii D.} and Abramov, {Maxim V.}",
note = "V. D. Oliseenko and M. V. Abramov, {"}RuBERT Embeddings in the Task of Classifying User Posts on a Social Media,{"} 2022 XXV International Conference on Soft Computing and Measurements (SCM), 2022, pp. 31-33, doi: 10.1109/SCM55405.2022.9794844.; 25th International Conference on Soft Computing and Measurements, SCM 2022 ; Conference date: 25-05-2022 Through 27-05-2022",
year = "2022",
month = may,
day = "25",
doi = "10.1109/scm55405.2022.9794844",
language = "English",
isbn = "9781665496698",
pages = "31--33",
editor = "S. Shaposhnikov",
booktitle = "Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - RuBERT Embeddings in the Task of Classifying User Posts on a Social Media

AU - Oliseenko, Valerii D.

AU - Abramov, Maxim V.

N1 - V. D. Oliseenko and M. V. Abramov, "RuBERT Embeddings in the Task of Classifying User Posts on a Social Media," 2022 XXV International Conference on Soft Computing and Measurements (SCM), 2022, pp. 31-33, doi: 10.1109/SCM55405.2022.9794844.

PY - 2022/5/25

Y1 - 2022/5/25

N2 - This paper presents models for solving the problem of multiclass classification of user posts in a social media. These models are based on embeddings extracted from messages using the RuBert language model and a fully connected neural network built over it. The models presented are compared to a baseline model using long-Term short-Term memory neurons (LSTM). The results will improve the accuracy of the classification posts, which in turn will improve the accuracy of assessing the psychological characteristics users.

AB - This paper presents models for solving the problem of multiclass classification of user posts in a social media. These models are based on embeddings extracted from messages using the RuBert language model and a fully connected neural network built over it. The models presented are compared to a baseline model using long-Term short-Term memory neurons (LSTM). The results will improve the accuracy of the classification posts, which in turn will improve the accuracy of assessing the psychological characteristics users.

KW - analysis of social media posts

KW - fully connected neural network

KW - LSTM

KW - machine learning

KW - multi-class classification

KW - RuBert

KW - sentence embedding

UR - http://www.scopus.com/inward/record.url?scp=85133307104&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/4804cd2b-e69e-313a-99ff-862ab295b07d/

U2 - 10.1109/scm55405.2022.9794844

DO - 10.1109/scm55405.2022.9794844

M3 - Conference contribution

AN - SCOPUS:85133307104

SN - 9781665496698

SP - 31

EP - 33

BT - Proceedings of 2022 25th International Conference on Soft Computing and Measurements, SCM 2022

A2 - Shaposhnikov, S.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th International Conference on Soft Computing and Measurements, SCM 2022

Y2 - 25 May 2022 through 27 May 2022

ER -

ID: 99228938