Identifying the temporal dynamics of densification and sparsification in human contact networks
Abstract Temporal social networks of human interactions are preponderant in understanding the fundamental patterns of human behavior. In these networks, interactions occur locally between individuals (i.e., nodes) who connect with each other at different times, culminating into a complex system-wide...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-10-01
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| Series: | EPJ Data Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1140/epjds/s13688-022-00365-3 |
| _version_ | 1811226704072409088 |
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| author | Shaunette T. Ferguson Teruyoshi Kobayashi |
| author_facet | Shaunette T. Ferguson Teruyoshi Kobayashi |
| author_sort | Shaunette T. Ferguson |
| collection | DOAJ |
| description | Abstract Temporal social networks of human interactions are preponderant in understanding the fundamental patterns of human behavior. In these networks, interactions occur locally between individuals (i.e., nodes) who connect with each other at different times, culminating into a complex system-wide web that has a dynamic composition. Dynamic behavior in networks occurs not only locally but also at the global level, as systems expand or shrink due either to: changes in the size of node population or variations in the chance of a connection between two nodes. Here, we propose a numerical maximum-likelihood method to estimate population size and the probability of two nodes connecting at any given point in time. An advantage of the method is that it relies only on aggregate quantities, which are easy to access and free from privacy issues. Our approach enables us to identify the simultaneous (rather than the asynchronous) contribution of each mechanism in the densification and sparsification of human contacts, providing a better understanding of how humans collectively construct and deconstruct social networks. |
| first_indexed | 2024-04-12T09:29:45Z |
| format | Article |
| id | doaj.art-fb5f9d34fc2d4580b094ddb15a91db49 |
| institution | Directory Open Access Journal |
| issn | 2193-1127 |
| language | English |
| last_indexed | 2024-04-12T09:29:45Z |
| publishDate | 2022-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EPJ Data Science |
| spelling | doaj.art-fb5f9d34fc2d4580b094ddb15a91db492022-12-22T03:38:24ZengSpringerOpenEPJ Data Science2193-11272022-10-0111111510.1140/epjds/s13688-022-00365-3Identifying the temporal dynamics of densification and sparsification in human contact networksShaunette T. Ferguson0Teruyoshi Kobayashi1Graduate School of Economics, Kobe UniversityDepartment of Economics, Center for Computational Social Science, Kobe UniversityAbstract Temporal social networks of human interactions are preponderant in understanding the fundamental patterns of human behavior. In these networks, interactions occur locally between individuals (i.e., nodes) who connect with each other at different times, culminating into a complex system-wide web that has a dynamic composition. Dynamic behavior in networks occurs not only locally but also at the global level, as systems expand or shrink due either to: changes in the size of node population or variations in the chance of a connection between two nodes. Here, we propose a numerical maximum-likelihood method to estimate population size and the probability of two nodes connecting at any given point in time. An advantage of the method is that it relies only on aggregate quantities, which are easy to access and free from privacy issues. Our approach enables us to identify the simultaneous (rather than the asynchronous) contribution of each mechanism in the densification and sparsification of human contacts, providing a better understanding of how humans collectively construct and deconstruct social networks.https://doi.org/10.1140/epjds/s13688-022-00365-3Temporal networksDensification scalingHuman contacts |
| spellingShingle | Shaunette T. Ferguson Teruyoshi Kobayashi Identifying the temporal dynamics of densification and sparsification in human contact networks EPJ Data Science Temporal networks Densification scaling Human contacts |
| title | Identifying the temporal dynamics of densification and sparsification in human contact networks |
| title_full | Identifying the temporal dynamics of densification and sparsification in human contact networks |
| title_fullStr | Identifying the temporal dynamics of densification and sparsification in human contact networks |
| title_full_unstemmed | Identifying the temporal dynamics of densification and sparsification in human contact networks |
| title_short | Identifying the temporal dynamics of densification and sparsification in human contact networks |
| title_sort | identifying the temporal dynamics of densification and sparsification in human contact networks |
| topic | Temporal networks Densification scaling Human contacts |
| url | https://doi.org/10.1140/epjds/s13688-022-00365-3 |
| work_keys_str_mv | AT shaunettetferguson identifyingthetemporaldynamicsofdensificationandsparsificationinhumancontactnetworks AT teruyoshikobayashi identifyingthetemporaldynamicsofdensificationandsparsificationinhumancontactnetworks |