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Aguillo I.F.,Cybermetrics Laboratory | Bar-Ilan J.,Bar - Ilan University | Levene M.,Birkbeck, University of London | Ortega J.L.,VICYT CSIC
Scientometrics | Year: 2010

Recently there is increasing interest in university rankings. Annual rankings of world universities are published by QS for the Times Higher Education Supplement, the Shanghai Jiao Tong University, the Higher Education and Accreditation Council of Taiwan and rankings based on Web visibility by the Cybermetrics Lab at CSIC. In this paper we compare the rankings using a set of similarity measures. For the rankings that are being published for a number of years we also examine longitudinal patterns. The rankings limited to European universities are compared to the ranking of the Centre for Science and Technology Studies at Leiden University. The findings show that there are reasonable similarities between the rankings, even though each applies a different methodology. The biggest differences are between the rankings provided by the QS-Times Higher Education Supplement and the Ranking Web of the CSIC Cybermetrics Lab. The highest similarities were observed between the Taiwanese and the Leiden rankings from European universities. Overall the similarities are increased when the comparison is limited to the European universities. © 2010 Akadémiai Kiadó, Budapest, Hungary.


Ortega J.L.,VICYT CSIC | Aguillo I.F.,Cybermetrics Laboratory
Journal of the American Society for Information Science and Technology | Year: 2012

This paper introduces a keyword map of the labels used by the scientists registered in the Google Scholar Citations (GSC) database from December 2011. In all, 15,000 random queries were formulated to GSC to obtain a list of 26,682 registered users. From this list a network graph of 6,660 labels was built and classified according to the Scopus Subject Area classes. Results display a detailed label map of the most used (>15 times) tags. The structural analysis shows that the core of the network is occupied by computer science-related disciplines that account for the most used and shared labels. This core is surrounded by clusters of disciplines related or close to computing such as Information Sciences, Mathematics, or Bioinformatics. Classical areas such as Chemistry and Physics are marginalized in the graph. It is suggested that GSC would in the future be an accurate source to map Science because it is based on the labels that scientists themselves use to describe their own research activity. © 2012 ASIS&T.


Ortega J.L.,VICYT CSIC | Aguillo I.F.,Cybermetrics Laboratory
Journal of the Association for Information Science and Technology | Year: 2014

This article offers a comparative analysis of the personal profiling capabilities of the two most important free citation-based academic search engines, namely, Microsoft Academic Search (MAS) and Google Scholar Citations (GSC). Author profiles can be useful for evaluation purposes once the advantages and the shortcomings of these services are described and taken into consideration. In total, 771 personal profiles appearing in both the MAS and the GSC databases were analyzed. Results show that the GSC profiles include more documents and citations than those in MAS but with a strong bias toward the information and computing sciences, whereas the MAS profiles are disciplinarily better balanced. MAS shows technical problems such as a higher number of duplicated profiles and a lower updating rate than GSC. It is concluded that both services could be used for evaluation proposes only if they are applied along with other citation indices as a way to supplement that information. © 2014 ASIS&T.


Aguillo I.F.,Cybermetrics Laboratory | Ortega J.L.,VICYT CSIC | Fernandez M.,Cybermetrics Laboratory | Utrilla A.M.,Cybermetrics Laboratory
Scientometrics | Year: 2010

The Ranking Web of World Repositories (http://repositories.webometrics.info) is introduced. The objective is to promote Open access initiatives (OAI) supporting the use of repositories for scientific evaluation purposes. A set of metrics based on web presence, impact and usage is discussed. The Ranking is built on indicators obtained from web search engines following a model close to the Impact Factor one. The activity accounts for a 50% of the index, including number of pages, pdf files and items in Google Scholar database, while the visibility takes into account the external inlinks received by the repository (the other 50%). The Ranking provides the Top 300 repositories from a total of 592 worldwide, with a strong presence of US, German and British institutional repositories and the leadership of the large subject repositories. Results suggest the need to take into consideration other file formats and the usage information, an option is not feasible today. © 2010 Akadémiai Kiadó, Budapest, Hungary.


Ortega J.L.,VICYT CSIC | Aguillo I.F.,Cybermetric Laboratory
Aslib Proceedings: New Information Perspectives | Year: 2013

Purpose: The aim of this paper is to present network visualisation as a way to analyse and to test the design of a website. Design/methodology/approach: A network graph of the access to the webometrics.info site from its web logs was analysed. Several graphs (navigational and query graphs) with different added variables were explored. SNA indicators were used to extract the main findings of these networks. Findings: The results show the double structure of the two language versions, the central position of the search engines as hubs that distribute the access to every page, how the pages are grouped by their thematic and structural relationships, and which pages are less requested through search engines queries or are less visible. Research limitations/implications: The results are based on the web performance of only one website and therefore generalisation has to be cautious. Originality/value: The application of network visualisation and SNA indicators allows to explore the navigation of a website by users and to test how it is used. The graph representation makes possible an intuitive way to observe the structure of a website, the behaviour of users and information consumption. © Emerald Group Publishing Limited.


Ortega J.L.,VICYT CSIC | Aguillo I.F.,Cybermetrics Laboratory
Journal of Informetrics | Year: 2013

The purpose of this paper is to analyse and describe the topological properties of the institutional and national collaboration network from the profiles extracted from Google Scholar Citations (GSC). 19,912 unique profiles with " co-authors" were obtained from a web crawl performed in March 2012. Several statistical and network analysis techniques were used to map and analyse these collaboration relationships at the country and institution level. Results show that The United States dominates the world scientific map and that every research institution is grouped by national, geographical and cultural criteria. A clustering phenomenon based on the self-similarity and fractal properties of scale-free networks is also observed. We conclude that GSC is a suitable tool for collaboration studies only at macro level between countries and institutions. © 2013 Elsevier Ltd.

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