How old users are? Community analysis.

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How old users are? Community analysis. / Oliseenko, Valerii ; Korepanova, Anastasia.

In: CEUR Workshop Proceedings, Vol. 2782, 2020, p. 246-251.

Research output: Contribution to journal › Conference article › peer-review

BibTeX

@article{7fac5f15a09b4cfd95e6fc92ae1ca5de,

title = "How old users are? Community analysis.",

abstract = "The presented work is devoted to the development of an approach to the age inference for users on the online social network VK.com. This approach is based on an analysis of the communities that the user is a member of. The proposed method is based on the hypothesis that users join some of those communities that contain data about class, graduation from school, data about the group at the university, etc. and those that have users{\textquoteright} peers as members. The proposed approach allows for the age inference. The obtained results can benefit research on online social networks, as well as the task of discovering a user vulnerability through social networks.",

keywords = "Fuzzy algorithms, Information security, Social engineering attacks, Social networks, User age inference",

author = "Valerii Oliseenko and Anastasia Korepanova",

note = "Publisher Copyright: {\textcopyright} 2020 CEUR-WS. All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; Russian Advances in Fuzzy Systems and Soft Computing: Selected Contributions to the 8th International Conference on {"}Fuzzy Systems, Soft Soft Computing and Intelligent Technologies{"},FSSCIT 2020 ; Conference date: 29-06-2020 Through 01-07-2020",

year = "2020",

language = "English",

volume = "2782",

pages = "246--251",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "RWTH Aahen University",

}

RIS

TY - JOUR

T1 - How old users are? Community analysis.

AU - Oliseenko, Valerii

AU - Korepanova, Anastasia

PY - 2020

Y1 - 2020

N2 - The presented work is devoted to the development of an approach to the age inference for users on the online social network VK.com. This approach is based on an analysis of the communities that the user is a member of. The proposed method is based on the hypothesis that users join some of those communities that contain data about class, graduation from school, data about the group at the university, etc. and those that have users’ peers as members. The proposed approach allows for the age inference. The obtained results can benefit research on online social networks, as well as the task of discovering a user vulnerability through social networks.

AB - The presented work is devoted to the development of an approach to the age inference for users on the online social network VK.com. This approach is based on an analysis of the communities that the user is a member of. The proposed method is based on the hypothesis that users join some of those communities that contain data about class, graduation from school, data about the group at the university, etc. and those that have users’ peers as members. The proposed approach allows for the age inference. The obtained results can benefit research on online social networks, as well as the task of discovering a user vulnerability through social networks.

KW - Fuzzy algorithms

KW - Information security

KW - Social engineering attacks

KW - Social networks

KW - User age inference

UR - http://www.scopus.com/inward/record.url?scp=85099029215&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85099029215

VL - 2782

SP - 246

EP - 251

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - Russian Advances in Fuzzy Systems and Soft Computing: Selected Contributions to the 8th International Conference on "Fuzzy Systems, Soft Soft Computing and Intelligent Technologies",FSSCIT 2020

Y2 - 29 June 2020 through 1 July 2020

ER -

ID: 73115403

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