This study focuses on the comparison and selection of the similarity coefficient for comparing social circles of users. Comparison of the social environment is used in comparing profiles in various social networking cites and identifying those that belong to one user. Six similarity coefficients are compared using machine learning methods and mathematical statistics. The selected coefficient will allow us to more accurately compare social circles of users and increase efficiency of the binary classifier (logistic regression) determining pair of profiles in various social networking cite belonging to one user. In addition, results of this study can be used in the analysis of social networking cites, for example, in the tasks of social computing.
Translated title of the contributionПрименимость коэффициентов сходства в задаче сравнения социального окружения
Original languageEnglish
Title of host publication2020 XXIII International Conference on Soft Computing and Measurements (SCM)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages41-43
ISBN (Electronic)978-1-7281-9692-3
ISBN (Print)978-1-7281-9693-0
StateAccepted/In press - 2020
EventXXIII International Conference on Soft Computing and Measurements SCM’2020 - Санкт-Петербург, Russian Federation
Duration: 27 May 2020 → 29 May 2020

Conference

ConferenceXXIII International Conference on Soft Computing and Measurements SCM’2020
Abbreviated titleSCM 2020
Country/TerritoryRussian Federation
CityСанкт-Петербург
Period27/05/20 → 29/05/20

    Research areas

  • similarity coefficients, social networking cites, user identification, social engineering attacks, machine learning, Information Security, User protection

ID: 62728271