An analysis of significance of Revised Web Impact Factor for ranking the websites of state universities in Sri Lanka

S. Wimaladharma, H. Herath
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引用次数: 4

Abstract

The level of connectivity and accessibility of a university website and the amount of information it shares have become a competitive factor among the world universities. Nowadays, the World Wide Web considerably contributes in the presence of information of university websites. Due to the immense distribution of information over the World Wide Web, it has been a challenging task to measure the quality and the quantity of the information each university website shares. Therefore, measuring the web impact has become the most popular mechanism among the researchers. This study is to compare the significance of web impact of the state university websites in Sri Lanka based on the link analysis statistics obtained from well-known search engines, Google and Yahoo!. In this analysis the Revised Web Impact Factor, the ratio between the number of inlinks (external back links) and the number of web pages published in the website which are indexed by the search engines (not all pages of the website),was taken into account. The correlation coefficient between the rank of resultant Revised Web Impact Factors and Impact Factors taken from the Webometrics website derived by Cybermetrics Lab was calculated with the ninety percent of inference level. If an academic website increases its link density via Yahoo! Search engine, it is relatively significance for its Webometrics impact factor whereas Google indexing expresses less relevance for the Webometrics impact factor.
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修订后的网络影响因子对斯里兰卡国立大学网站排名的意义分析
大学网站的连通性和可访问性水平及其共享信息的数量已成为世界大学之间的竞争因素。如今,万维网在大学网站信息的存在方面做出了很大的贡献。由于万维网上信息的巨大分布,衡量每个大学网站共享的信息的质量和数量一直是一项具有挑战性的任务。因此,测量网络影响成为研究人员最常用的机制。本研究是通过对知名搜索引擎b谷歌和Yahoo!的链接分析统计,比较斯里兰卡国立大学网站网络影响的显著性。在此分析中,考虑了修订后的网络影响因子,即链接(外部反向链接)数量与网站上发布的被搜索引擎索引的网页数量(不是网站的所有页面)之间的比率。修正后的网络影响因子排名与Cybermetrics实验室从Webometrics网站获取的影响因子排名之间的相关系数以90%的推理水平计算。如果一个学术网站通过Yahoo!搜索引擎,其网络计量影响因子相对重要,而谷歌索引对网络计量影响因子的相关性较低。
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