New edition: July 2019
Second edition of 2019: Web data collected during July 2019
The July edition (2019.2.2) is built with the indicators obtained during this month in order to maintain the freshness of the data of the most current and updated Ranking of Universities.
IMPORTANT: We have received many requests from universities asking for returning to use the Google data as a source for the Presence indicator. The revised editions (after 2019.2.1) now uses Google instead of Ahrefs data.
This text is the most updated info about the ranking’s methodology. It always supersedes the contents provided in the general Methodology. It is also relevant the info provided in the Notes section.
IMPORTANT: Please, do NOT send anonymous requests using email accounts such gmail.com, yahoo.com or hotmail.com. We are not going to answer any of these messages. Twitter requests are not accepted.
If you wish contact to EDITOR my email address is firstname.lastname@example.org. You can check my experience and expertise about these topics accessing the scientific papers I authored as described in my Google Scholar Citations profile or in my OA repository profile.
We warmly thank information about BAD PRACTICES, but we do not discuss specific ranks or comment on comparative results with other HEIs
We devoted time for preparing this site contents explaining the ranking and its methodology. Please, as a courtesy READ our texts before asking trivial questions already answered in this website.
Info provided here supersedes the contents provided in Methodology
Please, take into account that the following information:
– Spanish edition is no longer updated. Please refer to the English version.
– Exclusion of universities is reserved for diploma-mills, fake or doubtful institutions. Our decisions regarding not inclusion are final and we do not make any email exchange about these issues. However the absence of an institution could be due to an error, so please send to us information about the gaps or mistakes.
– Universities without full 24/7 webservers availability are excluded. Our criteria are not to rank those universities failing to answer our ping requests from our facilities to their servers during two consecutive month requests.
– As previously informed, we also changed our policy regarding the universities with two or more central web domains, a bad practice that it is going to be even more penalized than before. Until now, all the main web domains of the university were ranked, but only the one with the better web indicators was published, even if this was the old or the not-preferred one in the central homepage. This procedure is still applied when both domains maintain their independence, but if the old domain redirects to the new one, this will be the one ranked and published. As expected, this is having strong (negative) impact on a few universities.
Changes in the calculation of indicators
Published figures are RANKS (lower is better), intended for showing individual performances, but they are not the values used in the calculations. Due to technical issues several key changes (marked in red) have been done, so the following tablae describes the current methodology:
|PRESENCE||Public knowledge shared||Size (number of pages) of the main webdomain of the institution. It includes all the subdomains that share the same (central/main) webdomain||5%|
|VISIBILITY||Web contents Impact||Number of external networks (subnets) linking to the institution’s webpages (normalized and then average value)|| Ahrefs
|Top cited researchers|| Number of citations from Top 100 authors (excl. 5 outliers)
See Transparent Ranking for additional info
| Google Scholar
| Number of papers amongst the top 10% most cited in the 26 disciplines
Data for the five year period: 2013-2017
A few relevant facts about the Ranking
Since 2004, the Ranking Web (or Webometrics Ranking) is published twice a year (data is collected during the first weeks of January and July for being public at the end of both months), covering more than 28,000 Higher Education Institutions worldwide. We intend to motivate both institutions and scholars to have a web presence that reflect accurately their activities. If the web performance of an institution is below the expected position according to their academic excellence, university authorities should reconsider their web, open access and transparency policy, promoting substantial increases of the volume and quality of their electronic publications.
Data is collected between 1 and 20 of January or July, depending of the edition. Each variable is obtained at least two times during that period and the maximum value is chosen for discarding mistakes or errors. Volatility of search engines is very high, so figures can be different and not easily replicated if the search is performed days later. Google info is very geographically biased, so for our purposes the data are collected using the google.com mirror domain, English as language of the interface and Madrid (Spain) as location.
Final publication is done about the END of January or July, usually not before the 28th. We reserve the right to correct minor errors, mainly those related to the names of institutions, but also specific problems with the data. As a general rule we do not discuss any figure or provide the raw values supporting specific ranks.
The Webometrics Rank of a university is strongly linked to the volume and quality of the contents it publishes on the Web.
During the last years we discovered and fight unethical practices intending to manipulate (improving) the ranks of certain universities. In many cases these bad practices are so serious that local authorities should be called, so we decided not to act unilaterally regarding these activities. Results for Presence and Visibility are showed AS THEY ARE COLLECTED and if you suspect any wrongdoing, please contact with the university head, local or national authorities and/or journalists.
Additional exclusion criteria
A few institutions, mostly religious affiliated “Colleges” in Philippines and Latin America are publishing web portals that cover all their education activities, including those from their Schools (Basic Education) and High Schools (Intermediate Education). It will be unfair to include in the Ranking these institutions for comparative purposes, even although most of the web contents were related to their Higher Education departments. We strongly advice these organizations to segregate with an independent domain their university-level activities if they wish to be included in future editions.
This text is the general introduction to the ranking methodology. However, this is a research project and we change the methodology according to new findings or the availability of sources.
If you find discrepancies, please refer to the most updated info that is usually included in the introduction to each new edition.
That info always supersedes the one presented here
The Ranking Web or Webometrics is the largest academic ranking of Higher Education Institutions. Since 2004 and every six months an independent, objective, free, open scientific exercise is performed by the Cybermetrics Lab (Spanish National Research Council, CSIC) for the providing reliable, multidimensional, updated and useful information about the performance of universities from all over the world based on their web presence and impact.
The Cybermetrics Lab has been developing quantitative studies on the academic web since the mid-nineties. A first indicator was presented during the EASST/4S conference in Bielefeld (1996) and the collection of web data from European universities started in 1999 supported by the EU funded project EICSTES. These efforts are a follow-up of our scientometric research started in 1994 that has been presented in the conferences of the International Society for Scientometrics and Informetrics (ISSI, 1995-2011) and the International Conferences on Science and Technology Indicators (STI-ENID, 1996-2012) and published in high impact journals (Journal of Informetrics, Journal of the American Society for Information Science and Technology, Scientometrics, Journal of Information Science, Information Processing & Management, Research Evaluation and others). In 1997 we started the edition of an all-electronic open access peer-reviewed journal, Cybermetrics, devoted to the publication of webometrics-related papers.
In 2003 after the publication of the Shanghai Jiatong University breakthrough ranking, the Academic Ranking of World Universities (ARWU), we decided to adopt the main innovations proposed by Liu and his team. The ranking will be built from publicly available web data, combining the variables into a composite indicator, and with a true global coverage. The first edition was published in 2004, it appears twice per year since 2006 and after 2008 the portal also includes webometrics rankings for research centers, hospitals, repositories and business schools.
Objectives and motivation
The original aim of the Ranking is to promote academic web presence, supporting the Open Access initiatives for increasing significantly the transfer of scientific and cultural knowledge generated by the universities to the whole Society. In order to achieve this objective, the publication of rankings is one of the most powerful and successful tools for starting and consolidating the processes of change in the academia, increasing the scholars’ commitment and setting up badly needed long term strategies
The objective is not to evaluate websites, their design or usability or the popularity of their contents according to the number of visits or visitors. Web indicators are considered as proxies in the correct, comprehensive, deep evaluation of the university global performance, taking into account its activities and outputs and their relevance and impact.
At the end a reliable rank is only possible if the web presence is a trustworthy mirror of the university. In the second decade of the 21st century the Web is key for the future of all the university missions, as it is already the most important scholarly communication tool, the future channel for the off-campus distance learning, the open forum for the community engagement and the universal showcase for attracting talent, funding and resources.
Philosophy and justification
Webometrics only publish a unique Ranking of Universities in every edition. The combination of indicators is the result of a careful investigation and it is not open to individual choosing by users without enough knowledge or expertise in this field. Other publishers provide series of very different rankings using exactly the same data in different fashions that is completely useless and very confusing.
Webometrics is a ranking of all the universities of the world, not only a few hundred institutions from the developed world. Of course, “World-class” universities usually are not small or very specialized institutions.
Webometrics is continuously researching for improving the ranking, changing or evolving the indicators and the weighting model to provide a better classification. It is a shame that a few rankings maintain stability between editions without correcting errors or tuning up indicators.
Rankings backed by a for-profit company exploiting rank-related business or with strong political links reflected in individual ranks should be checked with care.
Research only (bibliometrics) based rankings are biased against technologies, computer science, social sciences and humanities, disciplines that usually amounts for more than half of the scholars and students in a standard comprehensive university. Webometrics also measure, in an indirect way, other missions like teaching or the so-called third mission, considering not only the scientific impact of the university activities, but also the economic relevance of the technology transfer to industry, the community engagement (social, cultural, environmental roles) and even the political influence.
Webometrics uses link analysis for quality evaluation as it is a far more powerful tool than citation analysis or global surveys. In the first case, bibliometrics only counts formal recognition between peers, while links not only includes bibliographic citations but also third parties involvement with university activities. Surveys are not a suitable tool for World Rankings as there is not even a single individual with a deep (several semesters per institution), multi-institutional (several dozen), multidisciplinary (hard sciences, biomedicine, social sciences, technologies) experience in a representative sample (different continents) of universities worldwide.
Research output is also key topic for Webometrics, but including not only formal (e-journals, repositories) publications but also informal scholarly communication. Web publication is cheaper, maintaining the high standards of quality of peer review processes. It could also reach much larger potential audiences, offering access to scientific knowledge to researchers and institutions located in developing countries and also to third parties (economic, industrial, political or cultural stakeholders) in their local community.
We intend to motivate both institutions and scholars to have a web presence that reflect accurately their activities. If the web performance of an institution is below the expected position according to their academic excellence, university authorities should reconsider their web policy, promoting substantial increases of the volume and quality of their electronic publications.
Candidate students should use additional criteria if they are trying to choose university. Webometrics ranking correlates well with quality of education provided and academic prestige, but other non-academic variables need to be taken into account.
Composite indicators and Web Impact Factor
Probably one of the major contributions of the Shanghai Ranking was to introduce a composite indicator, combining with a weighting system a series of indicators. Traditional bibliometric indexes are built on ratios like the Garfield’s Journal Impact Factor that based on variables following power law distributions is useless for describing large and complex scenarios. The Ingwersen proposal in 1997 for a similarly designed Web Impact Factor (WIF) using a links/webpages (L/W) ratio is equally doomed by the mathematical artifacts that generates.
Following the Shanghai model we developed an indicator transforming the ratio L/W into the following formula aL+bW, where L & W should be normalized in advance and a & b are weights adding 100%. We strongly discouraged the use of WIF due to its severe shortcomings. The composite indicator can be designed with different sets of variables and weightings according to the developer’s needs and models.
Design and Weighting of Indicators
Webometrics uses an “a-priori” scientific model for building the composite indicator. Other rankings choose arbitrary weights for strongly dependent variables and even combine raw values with ratios. None of them follow a logical ratio between activity related and impact related variables, i.e. each group representing 50% of the total weighting. Referring to the individual variables, some of them have values larger than zero for only a few universities and others segregate universities according to differences so small that they are even lower than their error rates.
Prior to combination the values should be normalized, but the practice of using percentages is mostly incorrect due to the power law distribution of the data.
Webometrics log-normalize the variables before combining according to a ratio 1:1 between activity/presence and visibility/impact groups of indicators.
Advantages and shortcomings
Coverage. Webometrics is the largest ranking by number of HEIs analyzed, but there is no classification of the different institutional types, so research-intensive universities are listed together with community colleges or theological seminaries. However the rank segregates all of them so it is not difficult to build sub-rankings for those interested.
University missions. The direct measurement of teaching mission is virtually unfeasible and those evaluations based on surveys (subjective), ratios of students/scholars (data unreliable and results not segregating) or employment results (with many variables involved other than quality of teaching) should be avoided. Webometrics rank indirectly this mission using web presence as an indicator of the commitment of the scholars with their students. It is not perfect but the future of this mission is clearly in the web arena and any institution or individual not realizing that is losing ground very fast.
Big numbers. Quality of the data does not only depend of the source used, but also of the numbers involved. For example, the number of universities with more than one Nobel Prize is probably lower than 200 (including all of those granted since 1900) that makes very difficult to rank them correctly. The same applies to citation data, the most powerful bibliometric tool that is providing figures in the order of thousands and tens of thousands. The link data offer far larger big number, usually two or even three orders of magnitude larger. Certainly the web indicators are noisier but statistically they are better suited for uncovering patterns and discriminating larger number of institutions.
Size-dependent. There is no debate about this issue: The most popular rankings, including Webometrics, are size dependent, although size does not refer to number of scholars or students (Harvard or especially MIT are not large in that sense) but probably to resources (current funding, past funding reflected in buildings, laboratories or libraries). But this criticism is not correct as really none of the rankings are really measuring efficiency but global performance. The economic wealth of the nations can be measured in terms of GDP (USA, China, Japan) or in terms of GDP per capita (Luxembourg, Emirates, Norway), both indicators are correct but their objectives are completely different.
Bad naming practices. University managers are still fighting for convincing their authors to assign the correct affiliations in the scientific publications. Situation is not far better in the Web with several hundred institutions having more than one central webdomain, preserving active old domains, using alternative domains for international (English) contents or sharing domains with third parties. Even among those universities with only one domain, many of them change the domain frequently, sometimes without any apparent good reason for doing that. A strange relatively common situation is when those changes are for transferring a national top level domain to an “.edu” domain (that usually refers to a USA university!) even when the country has a clearly defined academic subdomain (edu.pl, edu.ua, ac.kr). These changes and, especially the preservation along the time of several domains, penalizes very severely in Webometrics ranking. But of course it is also a very misleading practice that decreases the web visibility of the universities. Probably it has not so strong effect on local populations, but it is really confusing for the global audiences.
Fake and non-accredited universities. We try to do the best for not including fake institutions, checking especially online, international and foreign branches if they have independent web domain or subdomain. Any suggestion on these issues is greatly welcomed.
For more information please contact:
Cybermetrics Lab – CSIC
28037 Madrid. SPAIN
– Aguillo, I. F.; Granadino, B.; Ortega, J. L.; Prieto, J. A. (2006). Scientific research activity and communication measured with cybermetric indicators. Journal of the American Society for the Information Science and Technology, 57(10): 1296 – 1302.
– Wouters, P.; Reddy, C. & Aguillo, I. F. (2006). On the visibility of information on the Web: an exploratory experimental approach. Research Evaluation, 15(2):107-115.
– Ortega, J L; Aguillo, I.F.; Prieto, JA. (2006). Longitudinal Study of Contents and Elements in the Scientific Web environment. Journal of Information Science, 32(4):344-351.
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– Aguillo, I. F.; Granadino, B.; Ortega, J.L. & Prieto, J.A. (2005). What the Internet says about Science. The Scientist, 19(14):10, Jul. 18, 2005.
– Kretschmer, H. & Aguillo, I. F. (2004). Visibility of collaboration on the Web. Scientometrics, 61(3): 405-426.
– Cothey V, Aguillo IF & Arroyo N (2006). Operationalising “Websites”: lexically, semantically or topologically?. Cybermetrics, 10(1): Paper 4. http://cybermetrics.cindoc.csic.es/articles/v10i1p4.pdf