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DSRS: Estimation and Forecasting of Journal Influence in the Science and Technology Domain via a Lightweight Quantitative Approach

机译:DsRs:科技期刊影响力的估算与预测   技术领域通过轻量级定量方法

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摘要

The evaluation of journals based on their influence is of interest fornumerous reasons. Various methods of computing a score have been proposed formeasuring the scientific influence of scholarly journals. Typically thecomputation of any of these scores involves compiling the citation informationpertaining to the journal under consideration. This involves significantoverhead since the article citation information of not only the journal underconsideration but also that of other journals for the recent few years need tobe stored. Our work is motivated by the idea of developing a computationallylightweight approach that does not require any data storage, yet yields a scorewhich is useful for measuring the importance of journals. In this paper, aregression analysis based method is proposed to calculate Journal InfluenceScore. Proposed model is validated using historical data from the SCImagoportal. The results show that the error is small between rankings obtainedusing the proposed method and the SCImago Journal Rank, thus proving that theproposed approach is a feasible and effective method of calculating scientificimpact of journals.
机译:出于多种原因,基于期刊的影响力对期刊进行评估很受关注。已经提出了各种计算分数的方法来测量学术期刊的科学影响力。通常,这些分数中任何一个的计算都涉及对所考虑期刊的引用信息进行汇编。这需要大量的开销,因为不仅需要存储考虑不足的期刊的文章引文信息,还需要存储最近几年其他期刊的文献引文信息。我们的工作受到开发一种轻量级计算方法的想法的启发,该方法不需要任何数据存储,但会产生一个分数,可用于衡量期刊的重要性。本文提出了一种基于回归分析的方法来计算Journal ImpactScore。使用来自SCImagoportal的历史数据验证了提出的模型。结果表明,该方法与SCImago期刊等级之间的排名误差很小,证明了该方法是计算期刊科学影响力的一种可行,有效的方法。

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