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BERT and ELMo in Task of Classifying Social Media Users Posts. / Oliseenko, Valerii D. ; Eirich, Michael ; Tulupyev, Alexander L. ; Tulupyeva, Tatiana V. .

Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). Springer Nature, 2022. p. 475-486 (Lecture Notes in Networks and Systems; Vol. 566).

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

Harvard

Oliseenko, VD, Eirich, M, Tulupyev, AL & Tulupyeva, TV 2022, BERT and ELMo in Task of Classifying Social Media Users Posts. in Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). Lecture Notes in Networks and Systems, vol. 566, Springer Nature, pp. 475-486, 6th International Scientific Conference “Intelligent Information Technologies for Industry”, Istanbul, Turkey, 31/10/22. https://doi.org/10.1007/978-3-031-19620-1_45

APA

Oliseenko, V. D., Eirich, M., Tulupyev, A. L., & Tulupyeva, T. V. (2022). BERT and ELMo in Task of Classifying Social Media Users Posts. In Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22) (pp. 475-486). (Lecture Notes in Networks and Systems; Vol. 566). Springer Nature. https://doi.org/10.1007/978-3-031-19620-1_45

Vancouver

Oliseenko VD, Eirich M, Tulupyev AL, Tulupyeva TV. BERT and ELMo in Task of Classifying Social Media Users Posts. In Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). Springer Nature. 2022. p. 475-486. (Lecture Notes in Networks and Systems). https://doi.org/10.1007/978-3-031-19620-1_45

Author

Oliseenko, Valerii D. ; Eirich, Michael ; Tulupyev, Alexander L. ; Tulupyeva, Tatiana V. . / BERT and ELMo in Task of Classifying Social Media Users Posts. Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). Springer Nature, 2022. pp. 475-486 (Lecture Notes in Networks and Systems).

BibTeX

@inproceedings{201f06c7c1364c38a2df6254fb26d0e0,
title = "BERT and ELMo in Task of Classifying Social Media Users Posts",
abstract = "This paper considers the problem of automating the previously presented scheme of classification of users{\textquoteright} posts in social media. Different variations of the embeddings obtained from the RuBERT and ELMo language models are used as input features of the classification. Theoretical significance lies in the adaptation of existing language models BERT and ELMo in order to improve the accuracy of solving the applied problem of posts classification. The practical significance is determined by further automation of the classification of users{\textquoteright} text posts, which will form the basis of the system for assessing the expression of their personality traits and, indirectly, vulnerabilities to social engineering attack.",
author = "Oliseenko, {Valerii D.} and Michael Eirich and Tulupyev, {Alexander L.} and Tulupyeva, {Tatiana V.}",
note = "Oliseenko, V.D., Eirich, M., Tulupyev, A.L., Tulupyeva, T.V. (2023). BERT and ELMo in Task of Classifying Social Media Users Posts. In: Kovalev, S., Sukhanov, A., Akperov, I., Ozdemir, S. (eds) Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI{\textquoteright}22). IITI 2022. Lecture Notes in Networks and Systems, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-031-19620-1_45; null ; Conference date: 31-10-2022 Through 06-11-2022",
year = "2022",
month = oct,
day = "31",
doi = "10.1007/978-3-031-19620-1_45",
language = "English",
isbn = "978-3-031-19619-5",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Nature",
pages = "475--486",
booktitle = "Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI{\textquoteright}22)",
address = "Germany",
url = "http://iiti.rgups.ru/",

}

RIS

TY - GEN

T1 - BERT and ELMo in Task of Classifying Social Media Users Posts

AU - Oliseenko, Valerii D.

AU - Eirich, Michael

AU - Tulupyev, Alexander L.

AU - Tulupyeva, Tatiana V.

N1 - Conference code: 6

PY - 2022/10/31

Y1 - 2022/10/31

N2 - This paper considers the problem of automating the previously presented scheme of classification of users’ posts in social media. Different variations of the embeddings obtained from the RuBERT and ELMo language models are used as input features of the classification. Theoretical significance lies in the adaptation of existing language models BERT and ELMo in order to improve the accuracy of solving the applied problem of posts classification. The practical significance is determined by further automation of the classification of users’ text posts, which will form the basis of the system for assessing the expression of their personality traits and, indirectly, vulnerabilities to social engineering attack.

AB - This paper considers the problem of automating the previously presented scheme of classification of users’ posts in social media. Different variations of the embeddings obtained from the RuBERT and ELMo language models are used as input features of the classification. Theoretical significance lies in the adaptation of existing language models BERT and ELMo in order to improve the accuracy of solving the applied problem of posts classification. The practical significance is determined by further automation of the classification of users’ text posts, which will form the basis of the system for assessing the expression of their personality traits and, indirectly, vulnerabilities to social engineering attack.

U2 - 10.1007/978-3-031-19620-1_45

DO - 10.1007/978-3-031-19620-1_45

M3 - Conference contribution

SN - 978-3-031-19619-5

T3 - Lecture Notes in Networks and Systems

SP - 475

EP - 486

BT - Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22)

PB - Springer Nature

Y2 - 31 October 2022 through 6 November 2022

ER -

ID: 102490400