Standard

Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. / Mamaev, Ivan ; Mitrofanova, Olga .

Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings: 9th Conference, AINL 2020, Helsinki, Finland, October 7–9, 2020, Proceedings. ed. / Andrey Filchenkov; Janne Kauttonen; Lidia Pivovarova. Cham : Springer Nature, 2020. p. 17-33 (Communications in Computer and Information Science; Vol. 1292 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Mamaev, I & Mitrofanova, O 2020, Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. in A Filchenkov, J Kauttonen & L Pivovarova (eds), Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings: 9th Conference, AINL 2020, Helsinki, Finland, October 7–9, 2020, Proceedings. Communications in Computer and Information Science, vol. 1292 CCIS, Springer Nature, Cham, pp. 17-33, 9th Conference on Artificial Intelligence and Natural Language, AINL 2020, Helsinki, Finland, 7/10/20. https://doi.org/10.1007/978-3-030-59082-6_2

APA

Mamaev, I., & Mitrofanova, O. (2020). Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. In A. Filchenkov, J. Kauttonen, & L. Pivovarova (Eds.), Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings: 9th Conference, AINL 2020, Helsinki, Finland, October 7–9, 2020, Proceedings (pp. 17-33). (Communications in Computer and Information Science; Vol. 1292 CCIS). Springer Nature. https://doi.org/10.1007/978-3-030-59082-6_2

Vancouver

Mamaev I, Mitrofanova O. Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. In Filchenkov A, Kauttonen J, Pivovarova L, editors, Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings: 9th Conference, AINL 2020, Helsinki, Finland, October 7–9, 2020, Proceedings. Cham: Springer Nature. 2020. p. 17-33. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-030-59082-6_2

Author

Mamaev, Ivan ; Mitrofanova, Olga . / Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings: 9th Conference, AINL 2020, Helsinki, Finland, October 7–9, 2020, Proceedings. editor / Andrey Filchenkov ; Janne Kauttonen ; Lidia Pivovarova. Cham : Springer Nature, 2020. pp. 17-33 (Communications in Computer and Information Science).

BibTeX

@inproceedings{ca9552f40e7a4b659db661dc7b0a57ee,
title = "Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus",
abstract = "This paper proposes a linguistically-rich approach to hidden community detection which was tested in experiments with the Russian corpus of VKontakte posts. Modern algorithms for hidden community detection are based on graph theory, these procedures leaving out of account the linguistic features of analyzed texts. The authors have developed a new hybrid approach to the detection of hidden communities, combining author-topic modeling and automatic topic labeling. Specific linguistic parameters of Russian posts were revealed for correct language processing. The results justify the use of the algorithm that can be further integrated with already developed graph methods.",
keywords = "Hidden communities, Corpus linguistics, Social networks, Author-topic models, Automatic topic labeling",
author = "Ivan Mamaev and Olga Mitrofanova",
note = "Mamaev I., Mitrofanova O. (2020) Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. In: Filchenkov A., Kauttonen J., Pivovarova L. (eds) Artificial Intelligence and Natural Language. AINL 2020. Communications in Computer and Information Science, vol 1292. Springer, Cham. https://doi.org/10.1007/978-3-030-59082-6_2; 9th Conference on Artificial Intelligence and Natural Language, AINL 2020, AINL 2020 ; Conference date: 07-10-2020 Through 09-10-2020",
year = "2020",
month = sep,
day = "30",
doi = "10.1007/978-3-030-59082-6_2",
language = "English",
isbn = "978-3-030-59081-9",
series = "Communications in Computer and Information Science",
publisher = "Springer Nature",
pages = "17--33",
editor = "Filchenkov, {Andrey } and Kauttonen, {Janne } and Pivovarova, {Lidia }",
booktitle = "Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings",
address = "Germany",

}

RIS

TY - GEN

T1 - Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus

AU - Mamaev, Ivan

AU - Mitrofanova, Olga

N1 - Mamaev I., Mitrofanova O. (2020) Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus. In: Filchenkov A., Kauttonen J., Pivovarova L. (eds) Artificial Intelligence and Natural Language. AINL 2020. Communications in Computer and Information Science, vol 1292. Springer, Cham. https://doi.org/10.1007/978-3-030-59082-6_2

PY - 2020/9/30

Y1 - 2020/9/30

N2 - This paper proposes a linguistically-rich approach to hidden community detection which was tested in experiments with the Russian corpus of VKontakte posts. Modern algorithms for hidden community detection are based on graph theory, these procedures leaving out of account the linguistic features of analyzed texts. The authors have developed a new hybrid approach to the detection of hidden communities, combining author-topic modeling and automatic topic labeling. Specific linguistic parameters of Russian posts were revealed for correct language processing. The results justify the use of the algorithm that can be further integrated with already developed graph methods.

AB - This paper proposes a linguistically-rich approach to hidden community detection which was tested in experiments with the Russian corpus of VKontakte posts. Modern algorithms for hidden community detection are based on graph theory, these procedures leaving out of account the linguistic features of analyzed texts. The authors have developed a new hybrid approach to the detection of hidden communities, combining author-topic modeling and automatic topic labeling. Specific linguistic parameters of Russian posts were revealed for correct language processing. The results justify the use of the algorithm that can be further integrated with already developed graph methods.

KW - Hidden communities

KW - Corpus linguistics

KW - Social networks

KW - Author-topic models

KW - Automatic topic labeling

UR - http://www.scopus.com/inward/record.url?scp=85092931033&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/558b6feb-0fd8-3c4c-8855-693ab9703356/

U2 - 10.1007/978-3-030-59082-6_2

DO - 10.1007/978-3-030-59082-6_2

M3 - Conference contribution

SN - 978-3-030-59081-9

T3 - Communications in Computer and Information Science

SP - 17

EP - 33

BT - Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings

A2 - Filchenkov, Andrey

A2 - Kauttonen, Janne

A2 - Pivovarova, Lidia

PB - Springer Nature

CY - Cham

T2 - 9th Conference on Artificial Intelligence and Natural Language, AINL 2020

Y2 - 7 October 2020 through 9 October 2020

ER -

ID: 71062226