Data analysis based on Latane theory and analysis of events changing in social networks. / Akhmetova, A. Zh; Batura, T. V.; La, L. L. et al.
In: Journal of Theoretical and Applied Information Technology, Vol. 97, No. 16, 31.08.2019, p. 4309-4319.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Data analysis based on Latane theory and analysis of events changing in social networks
AU - Akhmetova, A. Zh
AU - Batura, T. V.
AU - La, L. L.
AU - Murzin, F. A.
N1 - Publisher Copyright: © 2005 – ongoing JATIT & LLS
PY - 2019/8/31
Y1 - 2019/8/31
N2 - The article describes the main methods and algorithms for analyzing user data from social networks. Special attention is paid to the method of measuring informational influence between users in a social network. In the process of analyzing social networks, it is advisable to consider a number of numerical and non-numerical characteristics, relations and sets that are naturally associated with network users and the messages circulating in it. The quantitative characteristics, relationships, and sets that are computable from data obtained from social networks, such as numeric single characteristics, non-numeric characteristics, sets, and numerical characteristics associated with sets, are presented. Modifications of the theory of dynamic social influence of Latane are proposed. The formulas describing the amount of social pressure directed at the individual for different situations have been modified. The method of R/S analysis, which can be applied to predict the change of events in social networks, is proposed. This method of time series analysis allows you to determine whether the time series is random or persistent, that is, having long-term memory. The article briefly describes the developed software package that allows to extract information from social networks, to process, analyze and visualize data. Testing was carried out on the data obtained from the social network vkontakte.
AB - The article describes the main methods and algorithms for analyzing user data from social networks. Special attention is paid to the method of measuring informational influence between users in a social network. In the process of analyzing social networks, it is advisable to consider a number of numerical and non-numerical characteristics, relations and sets that are naturally associated with network users and the messages circulating in it. The quantitative characteristics, relationships, and sets that are computable from data obtained from social networks, such as numeric single characteristics, non-numeric characteristics, sets, and numerical characteristics associated with sets, are presented. Modifications of the theory of dynamic social influence of Latane are proposed. The formulas describing the amount of social pressure directed at the individual for different situations have been modified. The method of R/S analysis, which can be applied to predict the change of events in social networks, is proposed. This method of time series analysis allows you to determine whether the time series is random or persistent, that is, having long-term memory. The article briefly describes the developed software package that allows to extract information from social networks, to process, analyze and visualize data. Testing was carried out on the data obtained from the social network vkontakte.
KW - Analysis Of Social Networks
KW - Data Analysis
KW - Latane Theory
KW - The Internet
KW - Vkontakte
UR - http://www.scopus.com/inward/record.url?scp=85073058986&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85073058986
VL - 97
SP - 4309
EP - 4319
JO - Journal of Theoretical and Applied Information Technology
JF - Journal of Theoretical and Applied Information Technology
SN - 1992-8645
IS - 16
ER -
ID: 34999487