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首页> 外文期刊>International Journal of Innovation and Technology Management >MODELING CITATION DIFFUSION: INNOVATION MANAGEMENT LITERATURE
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MODELING CITATION DIFFUSION: INNOVATION MANAGEMENT LITERATURE

机译：建模引文扩散：创新管理文学

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摘要

Citation patterns are important to understanding the spread of technological ideas as science is essentially a cumulative activity. One feature only now being appreciated is the obsolescence or ageing patterns in citations and the insights their study can bring. There have been a number of studies examining, predicting, modeling and plotting citation delays, ageing and the publication cycle. These normally apply lognormal, log-logistic and Weibull distributions to scientific papers. This paper adds to this body of work by examining a set of 18 other distributions, and tests their predictive power on a new data set based on 10 years of ISI Citation data for 10 innovation centered journals. The resulting grouping of journals appears to be a useful proxy for academic-practitioner involvement and warrants further investigation. The finding that the three-parameter Inverse Gaussian provides the best fit to the data extends the understanding of this process. As well as allowing the classification of literature, this improved representation of citation obsolescence will allow us to predict earlier and more precisely those scientific ideas which are generating noteworthy attention or may be suitable for early exploitation.
机译：引用方式对于理解技术思想的传播很重要，因为科学本质上是一项累积活动。现在仅被赞赏的一个特征是引用中的过时或老化模式及其研究可以带来的见解。已经有许多研究检查，预测，建模和绘制引文延迟，老化和出版周期。这些通常将对数正态，对数对数和Weibull分布应用于科学论文。本文通过检查一组其他18种分布来增加这一工作范围，并基于10年以ISI Citation数据为基础的10种以创新为中心的期刊，在一个新数据集上测试其预测能力。由此产生的期刊分类似乎是学术从业人员参与的有用代理，需要进一步调查。三参数逆高斯函数最适合数据的发现扩展了对该过程的理解。除了允许对文献进行分类之外，这种改进的引文过时表示方法还使我们能够更早，更准确地预测那些引起关注或可能适合早期利用的科学思想。

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