SocSig (Social Signature Phenomenon on Virtual Social Network Users' Data)
1 PHENOMENON of Social Signature in Social Network Users' Data
Project leader: Larisa Mararitsa
Participants: Yadviga Sinyavskaya, Maxim Terpilovsky, Olesya Koltsova, Sergey Pashakhin
Previous participants: Sergey Titov, Maxim Koltsov
The project studies the significance of online friends and their roles in individuals' lives. Study of the factors of emotional closeness between users and their online environment and identifying specific friendship markers can improve our understanding of dynamics strengthening social connections; refine models predicting or explaining the formation of friendships. The project examines how online relationships unfold within natural cognitive limits imposed on human communication. In this context, we aim to replicate the phenomenon of social signature found in the study of J. Saramaki and colleagues (2014) and to test and develop ideas about the layered structure of the human social environment expressed by A. Sutcliffe and colleagues (2012), using data on communication from the online social network Vkontakte. The phenomenon of social signature suggests that: (1) it is possible to identify functional 'layers'; in the social environment that are similar in their quantitative characteristics in different people; (2) the quantitative parameters of these layers in a person are stable; they do not change even during important events in his life. The layers differ in the nature of connections of their constituents and the function they perform for the person: from providing security to providing information. To test the stability of a person's communication pattern with other people, we collected data on 'friends'; from an online social network and the volume of directed communication (retrospective data on correspondence over the past three years). The functional and emotional substance of the relations is studied with the help of a specially designed questionnaire, where the participants themselves evaluate the ties with each of the ego-network agents. Additionally, we collect and analyse information about the ego-network structure and online behaviour on the online social network. The study was pre-registered with OSF in January 2018.
Participants: Yadviga Sinyavskaya, Dari Batozhargalova
In the second project, self-reported data on individuals' relationships with their online friends was combined with their network representation (ego networks). This triangulation allows us to solve the classic problem for sociological research of predicting the strength of a social connection (tie strength prediction). In the current study, we focus on network centrality metrics as a predictor of emotional closeness and trust in interpersonal relationships. As a methodological basis for the study, the capabilities of classical machine learning methods and statistical modelling methods designed for network data (ERGM) will be compared.
Project leader: Larisa Mararitsa
Participants: Yadviga Sinyavskaya, Maxim Terpilovsky, Olesya Koltsova, Sergey Pashakhin
Previous participants: Sergey Titov, Maxim Koltsov
The project studies the significance of online friends and their roles in individuals' lives. Study of the factors of emotional closeness between users and their online environment and identifying specific friendship markers can improve our understanding of dynamics strengthening social connections; refine models predicting or explaining the formation of friendships. The project examines how online relationships unfold within natural cognitive limits imposed on human communication. In this context, we aim to replicate the phenomenon of social signature found in the study of J. Saramaki and colleagues (2014) and to test and develop ideas about the layered structure of the human social environment expressed by A. Sutcliffe and colleagues (2012), using data on communication from the online social network Vkontakte. The phenomenon of social signature suggests that: (1) it is possible to identify functional 'layers'; in the social environment that are similar in their quantitative characteristics in different people; (2) the quantitative parameters of these layers in a person are stable; they do not change even during important events in his life. The layers differ in the nature of connections of their constituents and the function they perform for the person: from providing security to providing information. To test the stability of a person's communication pattern with other people, we collected data on 'friends'; from an online social network and the volume of directed communication (retrospective data on correspondence over the past three years). The functional and emotional substance of the relations is studied with the help of a specially designed questionnaire, where the participants themselves evaluate the ties with each of the ego-network agents. Additionally, we collect and analyse information about the ego-network structure and online behaviour on the online social network. The study was pre-registered with OSF in January 2018.
2. NETWORK CORRELATES OF PERCEIVED EMOTIONAL CLOSEness AND TRUST IN INTERPERSONAL RELATIONSHIPS
Participants: Yadviga Sinyavskaya, Dari Batozhargalova
In the second project, self-reported data on individuals' relationships with their online friends was combined with their network representation (ego networks). This triangulation allows us to solve the classic problem for sociological research of predicting the strength of a social connection (tie strength prediction). In the current study, we focus on network centrality metrics as a predictor of emotional closeness and trust in interpersonal relationships. As a methodological basis for the study, the capabilities of classical machine learning methods and statistical modelling methods designed for network data (ERGM) will be compared.
Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!
To be used only for spelling or punctuation mistakes.