User ratings analysis in social networks through a hypernetwork method
© 2015 Elsevier B.V. All rights reserved. This study utilizes the critical properties of a complex social network to reveal its intrinsic characteristics and the laws governing the way information propagates across the network to identify the central, active users and opinion leaders. The hypernetwo...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Elsevier Ltd
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/26060 |
| _version_ | 1848751878251216896 |
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| author | Suo, Q. Sun, S. Hajli, N. Love, Peter |
| author_facet | Suo, Q. Sun, S. Hajli, N. Love, Peter |
| author_sort | Suo, Q. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2015 Elsevier B.V. All rights reserved. This study utilizes the critical properties of a complex social network to reveal its intrinsic characteristics and the laws governing the way information propagates across the network to identify the central, active users and opinion leaders. The hypernetwork method is applied to analyze user ratings in social networks (SNSs). After introducing the concept of a hypernetwork and its topological characteristics such as node degree, the strength of the node and node hyperdegree, collaborative recommendations in hypernetworks are formulated based on the topological characteristics. Finally, the new method developed is applied to analyze data from the Douban social network. In this hypernetwork, users are defined as hyperedges and the objects as nodes. Three hypernetworks focused on reviews of books, movies and music were constructed using the proposed method and found to share a similar law of trends. These topological characteristics are clearly an effective way to reflect the relationship between users and objects. This research will enable SNSs providers to offer better object resource management and a personalized service for users, as well as contributing to empirical analyses of other similar SNSs. |
| first_indexed | 2025-11-14T07:59:43Z |
| format | Journal Article |
| id | curtin-20.500.11937-26060 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:59:43Z |
| publishDate | 2015 |
| publisher | Elsevier Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-260602017-09-13T15:23:29Z User ratings analysis in social networks through a hypernetwork method Suo, Q. Sun, S. Hajli, N. Love, Peter © 2015 Elsevier B.V. All rights reserved. This study utilizes the critical properties of a complex social network to reveal its intrinsic characteristics and the laws governing the way information propagates across the network to identify the central, active users and opinion leaders. The hypernetwork method is applied to analyze user ratings in social networks (SNSs). After introducing the concept of a hypernetwork and its topological characteristics such as node degree, the strength of the node and node hyperdegree, collaborative recommendations in hypernetworks are formulated based on the topological characteristics. Finally, the new method developed is applied to analyze data from the Douban social network. In this hypernetwork, users are defined as hyperedges and the objects as nodes. Three hypernetworks focused on reviews of books, movies and music were constructed using the proposed method and found to share a similar law of trends. These topological characteristics are clearly an effective way to reflect the relationship between users and objects. This research will enable SNSs providers to offer better object resource management and a personalized service for users, as well as contributing to empirical analyses of other similar SNSs. 2015 Journal Article http://hdl.handle.net/20.500.11937/26060 10.1016/j.eswa.2015.05.054 Elsevier Ltd restricted |
| spellingShingle | Suo, Q. Sun, S. Hajli, N. Love, Peter User ratings analysis in social networks through a hypernetwork method |
| title | User ratings analysis in social networks through a hypernetwork method |
| title_full | User ratings analysis in social networks through a hypernetwork method |
| title_fullStr | User ratings analysis in social networks through a hypernetwork method |
| title_full_unstemmed | User ratings analysis in social networks through a hypernetwork method |
| title_short | User ratings analysis in social networks through a hypernetwork method |
| title_sort | user ratings analysis in social networks through a hypernetwork method |
| url | http://hdl.handle.net/20.500.11937/26060 |