This paper aims at an important task of computing the webometrics university ranking and investigating if there exists a correlation between webometrics university ranking and the rankings provided by the world prominent university rankers such as QS world university ranking, for the time period of 2005–2016. However, the webometrics portal provides the required data for the recent years only, starting from 2012, which is insufficient for such an investigation. The rest of the required data can be obtained from the internet archive. However, the existing data extraction tools are incapable of extracting the required data from internet archive, due to unusual link structure that consists of web archive link, year, date, and target links. We developed an internet archive scrapper and extract the required data, for the time period of 2012–2016. After extracting the data, the webometrics indicators were quantified, and the universities were ranked accordingly. We used correlation coefficient to identify the relationship between webometrics university ranking computed by us and the original webometrics university ranking, using the spearman and pearson correlation measures. Our findings indicate a strong correlation between ours and the webometrics university rankings, which proves that the applied methodology can be used to compute the webometrics university ranking of those years for which the ranking is not available, i.e., from 2005 to 2011. We compute the webometrics ranking of the top 30 universities of North America, Europe and Asia for the time period of 2005–2016. Our findings indicate a positive correlation for North American and European universities, but weak correlation for Asian universities. This can be explained by the fact that Asian universities did not pay much attention to their websites as compared to the North American and European universities. The overall results reveal the fact that North American and European universities are higher in rank as compared to Asian universities. To the best of our knowledge, such an investigation has been executed for the very first time by us and no recorded work resembling this has been done before.

中文翻译：

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网络计量学：大学社交媒体存在的演变

本文旨在计算 webometrics 大学排名的重要任务，并调查 webometrics 大学排名与 QS 世界大学排名等世界著名大学排名提供的排名之间是否存在相关性，2005-2016 年时间段。但是，Webometrics 门户网站仅提供了从 2012 年开始的最近几年所需的数据，不足以进行此类调查。其余所需的数据可以从互联网档案中获得。然而，现有的数据提取工具无法从互联网档案中提取所需的数据，这是由于由网络档案链接、年份、日期和目标链接组成的不寻常的链接结构。我们开发了一个互联网档案抓取工具并提取了 2012 年至 2016 年期间所需的数据。提取数据后，对网络计量指标进行量化，并对大学进行相应排名。我们使用相关系数来确定我们计算的 webometrics 大学排名与原始 webometrics 大学排名之间的关系，使用 spearman 和 pearson 相关度量。我们的研究结果表明我们的排名与 webometrics 大学排名之间存在很强的相关性，这证明所应用的方法可用于计算排名不可用的那些年份的 webometrics 大学排名，即从 2005 年到 2011 年。我们计算2005-2016 年北美、欧洲和亚洲前 30 所大学的 webometrics 排名。我们的研究结果表明，北美和欧洲的大学呈正相关，但亚洲大学的相关性较弱。这可以解释为，与北美和欧洲大学相比，亚洲大学不太关注他们的网站。总体结果表明，与亚洲大学相比，北美和欧洲大学的排名更高。据我们所知，这样的调查是我们第一次进行，以前没有做过类似的记录工作。