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Finding leaders from opinion networks

机译:从意见网络中寻找领导者

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摘要

This paper is motivated to utilize results from opinion mining to facilitate social network analysis. We introduce the concept of opinion networks and propose a PageRank-like algorithm, named OpinionRank, to rank the nodes in an opinion network. This proposed approach has been applied to real-world datasets and initial experiments indicate that the sentiment information is helpful for finding leaders of online communities and that the OpinionRank method outperforms benchmark methods that ignore sentiment information.
机译:本文旨在利用观点挖掘的结果来促进社交网络分析。我们介绍了意见网络的概念,并提出了一种类似PageRank的算法,称为OpinionRank,用于对意见网络中的节点进行排名。此提议的方法已应用于现实世界的数据集,初步实验表明,情感信息有助于寻找在线社区的领导者,而OpinionRank方法的性能优于忽略情感信息的基准方法。

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