以迴歸分析探討電子學術期刊影響係數與網站排名之關聯

Numerical Correlation between Impact Factor and Web Ranking of Electronic Scientific Journals Using Regression Analysis

本研究試圖以迴歸分析方法探討電子學術期刊網站排名與其影響係數兩者間的相關性，使用迴歸分析得以調查與預測學術期刊於全球資訊網中的網站排名以及期刊影響係數兩者間的數值關係。研究分析的樣本為57家出版商及其下的6,272種學術期刊，與其他非隸屬於出版商而獨立出版（StandaloneJournals）的50種學術期刊。本研究採用在全球資訊網中網站分類的兩種指標──Alexa排名、Statscrop排名，分別檢驗57家來自出版商與50種獨立期刊。本研究所使用的影響係數之主要來源為電子資料庫。研究發現電子學術期刊之影響係數與其在全球資訊網中的網站分類呈現高度正相關。此外，作為影響係數的函數之一的網站排名受到高斯函數或皮爾森相關係數低的有理函數影響，而呈現非線性相關。即使電子期刊的影響係數與網站排名間為高度相關，但仍然無法以網站排名來預測影響係數。

The present study attempts to examine the numerical correlation between web ranking of electronic scientific journals and impact factor of these journals using the method of regression analysis. Regression analysis allows the option of investigating and predicting the numerical relationship between website ranking of scientific journals on the World Wide Web and the value of impact factor of the journals. A sample of 57 publishers with 6,272 scientific journals and 50 standalone scientific journals was analyzed during research procedure. In this study, two different indicators about websites classification on World Wide Web were examined separately for 57 publishers and 50 standalone journals, Alexa rank and Statscrop rank. The electronic databases through the internet constitute the main information resources of this study about the impact factors. The general conclusion that arises is that the impact factor of electronic scientific journals illustrates a very strong positive correlation with classification of websites on the World Wide Web. Furthermore, it is concluded that the change of web ranking as a function of impact factor is governed by a Gaussian function or rational function with lower Pearson coefficient and presents non-linearly correlation. Even if there is very strong correlation between impact factor and web rank for electronic journals, the prediction of impact factor from web rank is not possible and presents many divergences.