The predictive value of young and old links in a social network

Hung Hsuan Chen, David J. Miller, C. Lee Giles

研究成果: 書貢獻/報告類型會議論文篇章同行評審

5 引文 斯高帕斯(Scopus)

摘要

Recent studies show that vertex similarity measures are good at predicting link formation over the near term, but are less effective in predicting over the long term. This indicates that, generally, as links age, their degree of influence diminishes. However, few papers have systematically studied this phenomenon. In this paper, we apply a supervised learning approach to study age as a factor for link formation. Experiments on several real-world datasets show that younger links are more informative than older ones in predicting the formation of new links. Since older links become less useful, it might be appropriate to remove them when studying network evolution. Several previously observed network properties and network evolution phenomena, such as "the number of edges grows super-linearly in the number of nodes" and "the diameter is decreasing as the network grows", may need to be reconsidered under a dynamic network model where old, inactive links are removed.

原文???core.languages.en_GB???
主出版物標題Proceedings of the ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2013
發行者Association for Computing Machinery
頁面43-48
頁數6
ISBN(列印)9781450321914
DOIs
出版狀態已出版 - 2013
事件3rd ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2013 - New York, NY, United States
持續時間: 22 6月 201327 6月 2013

出版系列

名字Proceedings of the ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2013

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???event.eventtypes.event.conference???3rd ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2013
國家/地區United States
城市New York, NY
期間22/06/1327/06/13

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