UTILIZING MAXIMUM LIKELIHOOD FOR OPTIMAL PARTITIONING IN SOCIAL NETWORKS OF ELEVEN INDIVIDUALS
Ключевые слова:
Social Networks. Network Partitioning. Maximum Likelihood Method. Statistical Model. Inter-group Links. Parameter Estimation. Group Dynamics. Likelihood Function. Network Cohesion. Social Network Analysis. Node. Ties. Communication Optimization.. Network Modeling. Group Formation. Parameter Values. Computational Challenge. Likelihood MaximizationАннотация
The core purpose of the study is to explore how a specific statistical method, the 'maximum likelihood method', can be leveraged in a social network consisting of eleven individuals. The end goal is to correctly categorize these eleven individuals into two distinct groups. The idea behind using the maximum likelihood method is to ensure that these groups are optimally formed – such that they enable better communication and reliable cooperation within the network. The details about the process of utilizing the maximum likelihood method and the strategies adopted for partitioning are discussed in the manuscript. This includes creating an adjacency matrix to depict the social network, subsequently predicting two parameters: the likelihood of a link within a group and between groups, and applying maximum likelihood estimation to determine the optimal division.
Библиографические ссылки
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Мазалов В. В., Никитина Н. Н. Метод максимального правдоподобия для выделения сообществ в коммуникационных сетях // Вестник Санкт-Петербургского университета. Прикладная математика. Информатика. Процессы управления. 2018. Т. 14. Вып. 3. С. 200–214. https://doi.org/10.21638/11702/spbu10.2018.302.
