Statistical Methods and Applications in Social Networks
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 378
Special Issue Editors
Interests: statistics; social network analysis; text mining; multidimensional data analysis
Special Issue Information
Dear Colleagues,
Social network analysis (SNA) is now a mature field characterized by a strong interdisciplinary tendency. This discipline utilizes mathematical, statistical, and computational concepts and methods to analyze and visualize patterns of relationships within interconnected entities. The main objective of social network analysis is to understand the structure of social relationships, identify emerging patterns, and pinpoint the position and influence of key nodes within a network. SNA has applications in various fields such as sociology, psychology, management, epidemiology, and computer science, providing valuable insights into complex social dynamics and enhancing the design of interventions or strategies.
This Special Issue aims to investigate the leading areas of social network analysis and their application to multidisciplinary fields.
We welcome authors to submit manuscripts on statistical methods and applications in social networks, with emphasis on data collection and pre-treatment, network modelling, random graphs, longitudinal studies, personal networks, multilevel networks, community detection, blockmodelling, big data analysis, textual network, topic modelling, network analysis of social, economic, and business network. Overall, our primary focus is intersection of network science with other disciplines and their applications, and we look forward to sharing exciting work on this topic.
The Special Issue will bring together contributions from researchers in statistics, mathematics, sociology, economics, business organization, marketing, computer science, communication, and other scientific fields. Papers describing theoretical studies, complex data structures, as well as original applications in interdisciplinary and new fields, are welcome.
Prof. Giuseppe Giordano
Prof. Dr. Vladimir Batagelj
Guest Editors
Manuscript Submission Information
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Keywords
- blockmodeling
- community detection
- complex networks
- computational sociology
- digital society
- graph embedding
- graph visualization
- large networks
- social media
- textual and semantic networks
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