SOCIAL NETWORKS: EFFECTIVE METHODS OF DIVIDING INTO TWO AND THREE GROUPS
DOI:
https://doi.org/10.37547/Keywords:
Social networks. Social network analysis. Division into groups. Community detection methods. Algorithms. Polarization of opinions. Interest groups. Computing resources. Structure of social networks. The digital age. Maximum likelihood.Abstract
“Social networks: effective methods for dividing into two and three groups” is an objective look at current methods for analyzing social networks in order to identify subgroups or communities. The article examines in detail the use of various algorithms to determine the most clearly defined communities within social networks. Particular attention is paid to the importance of dividing into two or three groups to identify polarization of opinions or interest groups. The article also discusses the limitations of these methods related to the diversity of social network structures and the need for significant computing resources for large networks. In conclusion, the importance of updating and flexibility of approaches to analyzing social networks, taking into account the dynamic development of this area.
Downloads
References
1.Fortunato S., Community detection in graphs, Physics Reports, Volume 486, Issues 3–5, 2010, Pages 75-174, ISSN 0370-1573, https://doi.org/10.1016/j.physrep.2009.11.002.
2.Newman, Mark EJ. The structure and function of complex networks. SIAM review 45.2 (2003): 167-256. https://doi.org/10.1137/S003614450342480.
3.McPherson, Miller, Lynn Smith-Lovin, and James M. Cook. "Birds of a feather: Homophily in social networks." Annual review of sociology 27.1 (2001): 415-444.
4.Wasserman, Stanley, and Katherine Faust. "Social network analysis: Methods and applications." (1994).
5.Girvan, Michelle, and Mark EJ Newman. "Community structure in social and biological networks." Proceedings of the national academy of sciences 99.12 (2002): 7821-7826.
6.Weber L., Marketing to the Social Web: How Digital Customer Communities Build Your Business. ISBN:9781118258125 |DOI:10.1002/9781118258125. 2009
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Articles published in this journal are licensed under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). Under this license:
- Share: Copy and redistribute the material in any medium or format
- Adapt: Remix, transform, and build upon the material for any purpose, including commercially
Attribution required: You must give appropriate credit, provide a link to the license, and indicate if changes were made.
License URL: https://creativecommons.org/licenses/by/4.0/
Authors retain copyright of their work while granting the journal first publication rights.
