Down-Sampling Large-Scale Social Networks From Real-World Call Data
The rapid growth of digital communication technologies has led to the generation of large-scale social networks, particularly through the analysis of call data from mobile telecommunications. However, the sheer size of these networks poses significant challenges for computational analysis and storag...
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11048851/ |
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| author | Jinho Lee |
| author_facet | Jinho Lee |
| author_sort | Jinho Lee |
| collection | DOAJ |
| description | The rapid growth of digital communication technologies has led to the generation of large-scale social networks, particularly through the analysis of call data from mobile telecommunications. However, the sheer size of these networks poses significant challenges for computational analysis and storage. This paper presents a methodology for down-sampling large-scale social networks derived from real-world call data, using the c-core decomposition technique. By applying this technique, we efficiently reduce the size of the networks while preserving critical structural properties, such as degree distribution, clustering spectrum, and community structure. The analysis is conducted on data provided by a major Asian telecommunications company, encompassing over a year of call records. We demonstrate that the c-core decomposition not only scales down the networks effectively but also maintains the essential characteristics required for meaningful social network analysis. Our results show that down-sampling using c-core decomposition provides a robust framework for analyzing and interpreting large-scale social networks, offering valuable insights into the dynamics of human communication. |
| format | Article |
| id | doaj-art-1c66da077af14bf18775d7b99230ceaa |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-1c66da077af14bf18775d7b99230ceaa2025-08-20T03:31:40ZengIEEEIEEE Access2169-35362025-01-011311332911334210.1109/ACCESS.2025.358279211048851Down-Sampling Large-Scale Social Networks From Real-World Call DataJinho Lee0https://orcid.org/0000-0003-4192-3912College of Business Management, Hongik University, Sejong, South KoreaThe rapid growth of digital communication technologies has led to the generation of large-scale social networks, particularly through the analysis of call data from mobile telecommunications. However, the sheer size of these networks poses significant challenges for computational analysis and storage. This paper presents a methodology for down-sampling large-scale social networks derived from real-world call data, using the c-core decomposition technique. By applying this technique, we efficiently reduce the size of the networks while preserving critical structural properties, such as degree distribution, clustering spectrum, and community structure. The analysis is conducted on data provided by a major Asian telecommunications company, encompassing over a year of call records. We demonstrate that the c-core decomposition not only scales down the networks effectively but also maintains the essential characteristics required for meaningful social network analysis. Our results show that down-sampling using c-core decomposition provides a robust framework for analyzing and interpreting large-scale social networks, offering valuable insights into the dynamics of human communication.https://ieeexplore.ieee.org/document/11048851/Social network analysisdown-samplingc-core decompositioncall data networkslarge-scale networks |
| spellingShingle | Jinho Lee Down-Sampling Large-Scale Social Networks From Real-World Call Data IEEE Access Social network analysis down-sampling c-core decomposition call data networks large-scale networks |
| title | Down-Sampling Large-Scale Social Networks From Real-World Call Data |
| title_full | Down-Sampling Large-Scale Social Networks From Real-World Call Data |
| title_fullStr | Down-Sampling Large-Scale Social Networks From Real-World Call Data |
| title_full_unstemmed | Down-Sampling Large-Scale Social Networks From Real-World Call Data |
| title_short | Down-Sampling Large-Scale Social Networks From Real-World Call Data |
| title_sort | down sampling large scale social networks from real world call data |
| topic | Social network analysis down-sampling c-core decomposition call data networks large-scale networks |
| url | https://ieeexplore.ieee.org/document/11048851/ |
| work_keys_str_mv | AT jinholee downsamplinglargescalesocialnetworksfromrealworldcalldata |