arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1012.4870cs.DL
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发现作者影响:PageRank的观点

Discovering author impact: A PageRank perspective

Erjia Yan, Ying Ding

摘要:

这篇文章提供了另一种视角,通过将PageRank算法应用于合著网络来衡量作者的影响力。提出了一种考虑引文和合著网络拓扑结构的加权PageRank算法。我们测试此算法在不同的阻尼因子下,通过评估作者在信息计量学研究界的影响。此外,我们还将加权PageRank与国际科学计量学和信息计量学学会(ISSI)会议的h指数,引用和计划委员会(PC)成员进行了比较。研究结果表明,这种加权PageRank算法提供了可靠的结果,在衡量作者的影响。

英文摘要:

This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International Society for Scientometrics and Informetrics (ISSI) conferences. Findings show that this weighted PageRank algorithm provides reliable results in measuring author impact.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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