An interpretable approach for social network formation among heterogeneous agents
Complex networks can be a useful tool to investigate problems in social science. Here the authors use game theory to establish a network model and then use a machine learning approach to characterize the role of nodes within a social network.
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2018-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-018-07089-x |
| _version_ | 1819122484710998016 |
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| author | Yuan Yuan Ahmad Alabdulkareem Alex ‘Sandy’ Pentland |
| author_facet | Yuan Yuan Ahmad Alabdulkareem Alex ‘Sandy’ Pentland |
| author_sort | Yuan Yuan |
| collection | DOAJ |
| description | Complex networks can be a useful tool to investigate problems in social science. Here the authors use game theory to establish a network model and then use a machine learning approach to characterize the role of nodes within a social network. |
| first_indexed | 2024-12-22T06:53:12Z |
| format | Article |
| id | doaj.art-c5a02d4482f04595b7ba998a0e9dd4cb |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-22T06:53:12Z |
| publishDate | 2018-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-c5a02d4482f04595b7ba998a0e9dd4cb2022-12-21T18:35:04ZengNature PortfolioNature Communications2041-17232018-11-01911910.1038/s41467-018-07089-xAn interpretable approach for social network formation among heterogeneous agentsYuan Yuan0Ahmad Alabdulkareem1Alex ‘Sandy’ Pentland2Institute for Data, Systems, and Society, Massachusetts Institute of TechnologyCenter for Complex Engineering Systems, King Abdulaziz City for Science and Technology and Massachusetts Institute of TechnologyMedia Lab, Massachusetts Institute of TechnologyComplex networks can be a useful tool to investigate problems in social science. Here the authors use game theory to establish a network model and then use a machine learning approach to characterize the role of nodes within a social network.https://doi.org/10.1038/s41467-018-07089-x |
| spellingShingle | Yuan Yuan Ahmad Alabdulkareem Alex ‘Sandy’ Pentland An interpretable approach for social network formation among heterogeneous agents Nature Communications |
| title | An interpretable approach for social network formation among heterogeneous agents |
| title_full | An interpretable approach for social network formation among heterogeneous agents |
| title_fullStr | An interpretable approach for social network formation among heterogeneous agents |
| title_full_unstemmed | An interpretable approach for social network formation among heterogeneous agents |
| title_short | An interpretable approach for social network formation among heterogeneous agents |
| title_sort | interpretable approach for social network formation among heterogeneous agents |
| url | https://doi.org/10.1038/s41467-018-07089-x |
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