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 proceeding › Conference contribution › peer-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 -
