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Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks. / Oliseenko, Valerii D.; Tulupyeva, Tatiana V.

Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. ed. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2021. p. 46-48 9507148.

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

Harvard

Oliseenko, VD & Tulupyeva, TV 2021, Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks. in S Shaposhnikov (ed.), Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021., 9507148, Institute of Electrical and Electronics Engineers Inc., pp. 46-48, 24th International Conference on Soft Computing and Measurements, SCM 2021, St. Petersburg, Russian Federation, 26/05/21. https://doi.org/10.1109/scm52931.2021.9507148

APA

Oliseenko, V. D., & Tulupyeva, T. V. (2021). Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks. In S. Shaposhnikov (Ed.), Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021 (pp. 46-48). [9507148] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/scm52931.2021.9507148

Vancouver

Oliseenko VD, Tulupyeva TV. Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks. In Shaposhnikov S, editor, Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 46-48. 9507148 https://doi.org/10.1109/scm52931.2021.9507148

Author

Oliseenko, Valerii D. ; Tulupyeva, Tatiana V. / Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks. Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021. editor / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 46-48

BibTeX

@inproceedings{c6220f20c39b42cba870e92c34093cfa,
title = "Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks",
abstract = "This paper focuses on the issue of automating the multi-label classification of users' text posts in online social networks. This classification is based on previously developed criteria to correlate post types with the evaluation of the severity of psychological features of the user. The presented model for classification is based on a neural network with long short-term memory architecture. The results will help to partially automate the process of making recommendations to improve the protection of users from social engineering attacks. ",
keywords = "information security, multi-label classification, neural networks, online social networks, social engineering attacks, user protection",
author = "Oliseenko, {Valerii D.} and Tulupyeva, {Tatiana V.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 24th International Conference on Soft Computing and Measurements, SCM 2021 ; Conference date: 26-05-2021 Through 28-05-2021",
year = "2021",
month = may,
day = "26",
doi = "10.1109/scm52931.2021.9507148",
language = "English",
pages = "46--48",
editor = "S. Shaposhnikov",
booktitle = "Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

RIS

TY - GEN

T1 - Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks

AU - Oliseenko, Valerii D.

AU - Tulupyeva, Tatiana V.

N1 - Publisher Copyright: © 2021 IEEE.

PY - 2021/5/26

Y1 - 2021/5/26

N2 - This paper focuses on the issue of automating the multi-label classification of users' text posts in online social networks. This classification is based on previously developed criteria to correlate post types with the evaluation of the severity of psychological features of the user. The presented model for classification is based on a neural network with long short-term memory architecture. The results will help to partially automate the process of making recommendations to improve the protection of users from social engineering attacks.

AB - This paper focuses on the issue of automating the multi-label classification of users' text posts in online social networks. This classification is based on previously developed criteria to correlate post types with the evaluation of the severity of psychological features of the user. The presented model for classification is based on a neural network with long short-term memory architecture. The results will help to partially automate the process of making recommendations to improve the protection of users from social engineering attacks.

KW - information security

KW - multi-label classification

KW - neural networks

KW - online social networks

KW - social engineering attacks

KW - user protection

UR - http://www.scopus.com/inward/record.url?scp=85114021862&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/2173de62-6ab7-3796-b6a3-eea92fbad281/

U2 - 10.1109/scm52931.2021.9507148

DO - 10.1109/scm52931.2021.9507148

M3 - Conference contribution

AN - SCOPUS:85114021862

SP - 46

EP - 48

BT - Proceedings of 2021 24th International Conference on Soft Computing and Measurements, SCM 2021

A2 - Shaposhnikov, S.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th International Conference on Soft Computing and Measurements, SCM 2021

Y2 - 26 May 2021 through 28 May 2021

ER -

ID: 85483135