THE MAXIMUM REALIZATION METHOD OF COMMUNITY GROUPING IN SOCIAL NETWORKS
Keywords:
maximum likelihood, Graphics, Communication between teams, Teams section, Maple
Abstract
Identifying communities in social networks is one of the most important tasks nowadays. Social networks are especially relevant for networks represented by large-scale graphics. At the same time, it is important to use approximate methods that lead to near-optimal rather than optimal results within a given time. In this article, we propose to extract the communities based on the method of maximum likelihood similarity by representing them by letters. The community structure search algorithm is described and the performance of the algorithm is illustrated using examples of different views of the octagonal network.. Calculations were carried out using the Maple program.
References
1. 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.
2. Fortunato S., Barthelemy M. Resolution limit in community detection. Proceedings of the National Academy of Sciences USA, 2007, vol. 104(1), pp. 36–41.
3. Girvan M., Newman M.E. J. Community structure in social and biological networks. Proceedings of the National Academy of Sciences USA, 2002, vol. 99(12), pp. 7821–7826.
4. Copic J., Jackson M., Kirman A. Identifying community structures from network data via maximum likelihood methods // The B. E. Journal of Theoretical Economics. 2009. Vol. 9, iss. 1. P. 1635–1704.
2. Fortunato S., Barthelemy M. Resolution limit in community detection. Proceedings of the National Academy of Sciences USA, 2007, vol. 104(1), pp. 36–41.
3. Girvan M., Newman M.E. J. Community structure in social and biological networks. Proceedings of the National Academy of Sciences USA, 2002, vol. 99(12), pp. 7821–7826.
4. Copic J., Jackson M., Kirman A. Identifying community structures from network data via maximum likelihood methods // The B. E. Journal of Theoretical Economics. 2009. Vol. 9, iss. 1. P. 1635–1704.
Published
2023-05-18
How to Cite
Dilshodbek, Z., & Bektosh, S. (2023). THE MAXIMUM REALIZATION METHOD OF COMMUNITY GROUPING IN SOCIAL NETWORKS. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 4(5), 56-61. https://doi.org/10.17605/OSF.IO/5RQ2S
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