Proposal for a multilevel university cybermetric analysis model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-012-0868-5Universities’ online seats have gradually become complex systems of dynamic information where all their institutions and services are linked and potentially accessible. These online seats now constitute a central node around which universities construct and document their main activities and services. This information can be quantitative measured by cybermetric techniques in order to design university web rankings, taking the university as a global reference unit. However, previous research into web subunits shows that it is possible to carry out systemic web analyses, which open up the possibility of carrying out studies which address university diversity, necessary for both describing the university in greater detail and for establishing comparable ranking units. To address this issue, a multilevel university cybermetric analysis model is proposed, based on parts (core and satellite), levels (institutional and external) and sublevels (contour and internal), providing a deeper analysis of institutions. Finally the model is integrated into another which is independent of the technique used, and applied by analysing Harvard University as an example of use.Orduña Malea, E.; Ontalba Ruipérez, JA. (2013). Proposal for a multilevel university cybermetric analysis model. Scientometrics. 95(3):863-884. doi:10.1007/s11192-012-0868-5S863884953Acosta Márquez, T., Igartua Perosanz, J.J. & Gómez Isla, J. (2009). Páginas web de las universidades españolas. Enred: revista digital de la Universidad de Salamanca, 5 [online; discontinued].Aguillo, I. F. (1998). Hacia un concepto documental de sede web. El Profesional de la Información, 7(1–2), 45–46.Aguillo, I. F. (2009). Measuring the institutions’ footprint in the web. Library Hi Tech, 27(4), 540–556.Aguillo, I. F., Granadino, B., Ortega, J. L., & Prieto, J. A. (2006). Scientific research activity and communication measured with cybermetrics indicators. Journal of the American Society for Information Science and Technology, 57(10), 1296–1302.Aguillo, I. F., Ortega, J. L., & Fernández, M. (2008). Webometric Ranking of World Universities: introduction, methodology, and future developments. Higher Education in Europe, 33(2/3), 234–244.Ayan, N., Li, W.-S., & Kolak, O. (2002). Automatic extraction of logical domains in a web site. Data & Knowledge Engineering, 43(2), 179–205.Barjak, F., Li, X., & Thelwall, M. (2007). Which factors explain the Web impact of scientists’ personal homepages? Journal of the American Society for Information Science and Technology, 58(2), 200–211.Berners-Lee, T., & Fischetti, M. (2000). Tejiendo la Red. Madrid: Siglo XXI.Björneborn, L., & Ingwersen, P. (2004). Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14), 1216–1227.Buenadicha, M., Chamorro, A., Miranda, F. J., & González, O. R. (2001). A new web assessment index: Spanish Universities Analysis. Internet Research, 11(3), 226–234.Castells, M. (2001). La galaxia Internet. Barcelona: Plaza y Janés.Chu, H., He, S., & Thelwall, M. (2002). Library and Information Science Schools in Canada and USA: a Webometric perspective. Journal of Education for Library and Information Science, 43(2), 110–125.Crowston, K., & Williams, M. (2000). Reproduced and Emergent Genres of Communication on the World Wide Web. The Information Society: an International Journal, 16(3), 201–215.Goldfarb, A. (2006). The (teaching) role of universities in the diffusion of the Internet. International Journal of Industrial Organization, 24(2), 203–225.Ingwersen, P. (1998). The calculation of web impact factors. Journal of Documentation, 54(2), 236–243.Katz, R. N. (2008a). The tower and the cloud: Higher education in the age of cloud computing. USA: Educause.Katz, R. N. (2008b). The gathering cloud: is this the end of the middle. In R. N. Katz (Ed.), The tower and the cloud: Higher education in the age of cloud computing (p. 2008). USA: Educause.Li, X. (2005). National and international university departmental Web site interlinking: a webometric analysis. [Unpublished doctoral dissertation]. Wolverhampton, UK: University of Wolverhampton.Li, X., Thelwall, M., Musgrove, P., & Wilkinson, D. (2003). The relationship between the links/Web Impact Factors of computer science departments in UK and their RAE (Research Assessment Exercise) ranking in 2001. Scientometrics, 57(2), 239–255.Middleton, I., McConnell, M., & Davidson, G. (1999). Presenting a model for the structure and content of a University World Wide Web site. Journal of Information Science, 25(3), 217–219.Orduña-Malea, E. (2012). Propuesta de un modelo de análisis redinformétrico multinivel para el estudio sistémico de las universidades españolas (2010). Valencia: Polytechnic University of Valencia.Ortega, J. L., & Aguillo, Isidro. F. (2007). La web académica española en el contexto del Espacio Europeo de Educación Superior: estudio exploratorio. El profesional de la información, 16(5), 417–425.Pareja, V. M., Ortega, J. L., Prieto, J. A., Arroyo, N., & Aguillo, I. F. (2005). Desarrollo y aplicación del concepto de sede web como unidad documental de análisis en Cibermetría. Jornadas Españolas de Documentación, 9, 325–340.Saorín, T. (2012). Arquitectura de la dispersión: gestionar los riesgos cíclicos de fragmentación de las webs corporativas. Anuario ThinkEPI, 6, 281–287.Tang, R., & Thelwall, M. (2003). U.S. academic departmental Web-site interlinking: disciplinary differences. Library & Information Science Research, 25(4), 437–458.Tang, R., & Thelwall, M. (2004). Patterns of national and international web inlinks to US academic departments: an analysis of disciplinary variations. Scientometrics, 60(3), 475–485.Thelwall, M. (2002a). A research and institutional size based model for national university Web site interlinking. Journal of Documentation, 58(6), 683–694.Thelwall, M. (2002b). Conceptualizing documentation on the Web: an evaluation of different heuristic-based models for counting links between university web sites. Journal of the American Society for Information Science and Technology, 53(12), 995–1005.Thelwall, M. (2003). Web use and peer interconnectivity metrics for academic Web sites. Journal of Information Science, 29(1), 11–20.Thelwall, M. (2009). Introduction to Webometrics: quantitative web research for the social sciences. San Rafael: Morgan & Claypool.Thelwall, M., & Harries, G. (2004a). Can personal Web pages that link to universities yield information about the wider dissemination of research? Journal of Information Science, 30(3), 243–256.Thelwall, M., & Harries, G. (2004b). Do better scholars’ Web publications have significantly higher online impact? Journal of American Society for Information Science and Technology, 55(2), 149–159.Thelwall, M., Vaughan, L., & Björneborn, L. (2005). Webometrics. Annual Review of Information Science and Technology, 39, 81–135.Thomas, O., & Willet, P. (2000). Webometric analysis of Departments of librarianship and information science. Journal of Information Science, 26(6), 421–428.Tíscar, L. (2009). El papel de la universidad en la construcción de su identidad digital. Revista de universidad y sociedad del conocimiento, 6(1), 15–21.Van Vught, F. A. (2009). Diversity and differentiation in higher education. In F. Van Vught (Ed.), Mapping the higher education landscape: toward a European classification of higher education (pp. 1–16). The Netherlands: Springer.Yolku, O. (2001). Use of news articles and announcements on official websites of universities. Turkish Online Journal of Educational Technology, 10(2), 287–296

Cómo mejorar la visibilidad de la producción científica de una universidad en la web académica

Conferencias pronunciadas en la jornada organizada por la Universidad de Alicante el 15 de septiembre de 2014Tras comentar los cambios que se están produciendo en el proceso de comunicación científica y en el sistema de evaluación científica se proponen recomendaciones para mejorar la visibilidad y accesibilidad de la producción científica de autores, grupos de investigación, repositorios y de las web de las universidades. Se incide especialmente en la necesidad de elaborar perfles de autor en Google Scholar y en tomar medidas técnicas para que las páginas web de las universidades, los repositorios y los grupos de investigación se indicen correctamente en los buscadores académcios y especialmente en Google.Vicerectorat d’Investigació, Desenvolupament i Innovación de la Universidad de Alicant

Influence of language and file type on the web visibility of top European universities

Purpose The purpose of this paper is to detect whether both file type (a set of rich and web files) and language (English, Spanish, German, French and Italian) influence the web visibility of European universities. Design/methodology/approach A webometrics analysis of the top 200 European universities (as ranked in the Ranking web of World Universities) was carried out by a manual query for each official URL identified by using the Google search engine (April 2012). A correlation analysis between visibility and file format page count is offered according to language. Finally, a prediction of visibility is shown by using the SMOreg function. Findings The results indicate that Spanish and English are the languages that correlate most highly with web visibility. This correlation becomes greater though moderate when considering only PDF files. Research limitations/implications The results are limited due to the low correlation between overall page count and visibility. The lack of an accurate search engine that would assist in link counting procedures makes this process difficult. Originality/value An observed increase in correlation although moderate while analysing PDF files (in English and Spanish) is considered to be meaningful. This may indirectly confirm that specific file formats and languages generate different web visibility behaviour on European university web sites.Orduña Malea, E.; Ortega, JL.; Aguillo, IF. (2014). Influence of language and file type on the web visibility of top European universities. Aslib Journal of Information Management. 66(1):96-116. doi:10.1108/AJIM-02-2013-0018S96116661Aguillo, I.F. and Granadino, B. (2006), “Indicadores web para medir la presencia de las universidades en la Red”, Revista de universidad y Sociedad del Conocimiento, Vol. 3 No. 1, pp. 68-75.Aguillo, I.F. , Granadino, B. , Ortega, J.L. and Prieto, J.A. (2006), “Scientific research activity and communication measured with cybermetrics indicators”, Journal of the American Society for Information Science and Tecnology, Vol. 57 No. 10, pp. 1296-1302.Aguillo, I.F. , Ortega, J.L. and Fernández, M. (2008), “Webometric ranking of World universities: introduction, methodology, and future developments”, Higher Education in Europe, Vol. 33 Nos 2-3, pp. 233-244.Angus, E., Thelwall, M., & Stuart, D. (2008). General patterns of tag usage among university groups in Flickr. Online Information Review, 32(1), 89-101. doi:10.1108/14684520810866001Araujo Serna, L. and Martínez Romo, J. (2009), “Detección de Web Spam basada en la recuperación automática de enlaces”, Procesamiento del lenguaje natural, No. 42, pp. 39-46.Bar-Ilan, J. (2002), “Methods for measuring search engine performance over time”, Journal of the American Society for Information Science and Technology, Vol. 53 No. 4, pp. 308-319.Bar-Ilan, J. (2005), “What do we know about links and linking? A framework for studying links in academic environments”, Information Processing & Management, Vol. 41 No. 3, pp. 973-986.Cho, Y. and García-Molina, H. (2000), “The evolution of the web and implications for an incremental crawler”, Proceedings of the 26th International Conference on Very Large Data Bases, pp. 200-209.Fetterly, D. , Manasse, M. , Najork, M. and Wiener, J. (2003), “A large scale study of the evolution of web pages”, Proceedings of the Twelfth International Conference on World Wide Web, pp. 669-678.Garfield, E. (1967), “English – An international language for science?”, Current Contents, pp. 19-20.Gerrand, P. (2007), “Estimating linguistic diversity on the internet: a taxonomy to avoid pitfalls and paradoxes”, Journal of Computer-Mediated Communication, Vol. 12 No. 4, pp. 1298-1321.Ingwersen, P. (1998). The calculation of web impact factors. Journal of Documentation, 54(2), 236-243. doi:10.1108/eum0000000007167Koehler, W. (2004), “A longitudinal study of web pages continued: a consideration of document persistence”, Information Research, Vol. 9 No. 2.Kousha, K. , Thelwall, M. and Abdoli, M. (2012), “The role of online videos in research communication: a content analysis of YouTube videos cited in academic publications”, Journal of the American Society for Information Science and Technology, Vol. 63 No. 9, pp. 1710-1727.Kousha, K. , Thelwall, M. and Rezaie, S. (2010), “Using the web for research evaluation: the integrated online impact indicator”, Journal of Informetrics, Vol. 4 No. 1, pp. 124-135.Lawrence, S. and Giles, L. (1999), “Accessibility of information on the web”, Nature, Vol. 400, pp. 107-109.Lazarinis, F. (2007), “Web retrieval systems and the Greek language: do they have an understanding?”, Journal of information science, Vol. 33 No. 5, pp. 622-636.Lewandowski, D. (2008). Problems with the use of web search engines to find results in foreign languages. Online Information Review, 32(5), 668-672. doi:10.1108/14684520810914034Martins, B. and Silva, M.J. (2005), “Language identification in web pages”, Proceedings of the ACM Symposium of Applied Computing, Santa Fe, NM, ACM, New York, NY, pp. 764-768.Moukdad, H. and Cui, H. (2005), “How do search engines handle Chinese queries?”, Webology, Vol. 2 No. 3, p.Ntoulas, A. , Najork, M. , Manasse, M. and Fetterly, D. (2006), “Detecting spam web pages through content analysis”, Proceedings of the 15th International Conference on World Wide Web, AMA, New York, NY, pp. 83-92.O'Neill, E.T. , Lavoie, B.F. and Bennett, R. (2003), “Trends in the evolution of the public Web: 1998-2002”, D-Lib Magazine, Vol. 9 No. 4, available at: www.dlib.org/dlib/april03/lavoie/04lavoie.html (accessed 11 February 2013).Orduña-Malea, E. (2012), “Graphic, multimedia, and blog-content presence in the Spanish academic web-space”, Cybermetrics, Vol. 15, available at: http://cybermetrics.cindoc.csic.es/articles/v16i1p3.pdf (accessed 11 February 2013).Orduña-Malea, E. and Ontalba-Ruipérez, J-A. (2013), “Proposal for a multilevel university cybermetric analysis model”, Scientometrics, Vol. 95 No. 3, pp. 863-884.Orduña-Malea, E. , Serrano-Cobos, J. , Ontalba-Ruipérez, J-A. and Lloret-Romero, N. (2010), “Presencia y visibilidad web de las universidades públicas españolas”, Revista española de documentación científica, Vol. 33 No. 2, pp. 246-278.Payne, N. and Thelwall, M. (2007), “A longitudinal study of academic webs: growth and stabilization”, Scientometrics, Vol. 71 No. 3, pp. 523-539.Seeber, M. , Lepori, B. , Lomi, A. , Aguillo, I. and Barberio, V. (2012), “Factors affecting web links between European higher education institutions”, Journal of Informetrics, Vol. 6, pp. 435-447.Thelwall, M. (2008a), “Bibliometrics to webometrics”, Journal of Information Science, Vol. 34 No. 4, pp. 605-621.Thelwall, M. (2008b), “Quantitative comparisons of search engine results”, Journal of the American Society for Information Science and Technology, Vol. 59 No. 11, pp. 1702-1710.Thelwall, M. and Tang, R. (2003), “Disciplinary and linguistic considerations for academic web linking: an exploratory hyperlink mediated study with Mainland China and Taiwan”, Scientometrics, Vol. 58 No. 1, pp. 155-181.Thelwall, M. , Tang, R. and Price, L. (2003), “Linguistic patterns of academic web use in Western Europe”, Scientometrics, Vol. 56 No. 3, pp. 417-432.Vaughan, L. (2006), “Visualizing linguistic and cultural differences using web co-link data”, Journal of the American Society for Information Science and Technology, Vol. 57 No. 9, pp. 1178-1193.Vaughan, L. and Thelwall, M. (2004), “Search engine coverage bias: evidence and possible causes”, Information Processing & Management, Vol. 40 No. 4, pp. 693-707.Vaughan, L. and Zhang, Y. (2007), “Equal representation by search engines? A comparison of Web sites across countries and domains”, Journal of Computer-Mediated Communication, Vol. 12 No. 3, pp. 888-909.Wilkinson, D. , Harries, G. , Thelwall, M. and Price, L. (2003), “Motivations for academic web site interlinking: evidence for the web as a novel source of information on informal scholarly communication”, Journal of information science, Vol. 29 No. 1, pp. 49-56

Are web mentions accurate substitutes for inlinks for Spanish universities?

This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limitedurpose – Title and URL mentions have recently been proposed as web visibility indicators instead of inlink counts. The objective of this study is to determine the accuracy of these alternative web mention indicators in the Spanish academic system, taking into account their complexity (multi-domains) and diversity (different official languages). Design/methodology/approach – Inlinks, title and URL mentions from 76 Spanish universities were manually extracted from the main search engines (Google, Google Scholar, Yahoo!, Bing and Exalead). Several statistical methods, such as correlation, difference tests and regression models, were used. Findings – Web mentions, despite some limitations, can be used as substitutes for inlinks in the Spanish academic system, although these indicators are more likely to be influenced by the environment (language, web domain policy, etc.) than inlinks. Research limitations/implications – Title mentions provide unstable results caused by the multiple name variants which an institution can present (such as acronyms and other language versions). URL mentions are more stable, but they may present atypical points due to some shortcomings, the effect of which is that URL mentions do not have the same meaning as inlinks. Practical implications – Web mentions should be used with caution and after a cleaning-up process. Moreover, these counts do not necessarily signify connectivity, so their use in global web analysis should be limited. Originality/value – Web mentions have previously been used in some specific academic systems (US, UK and China), but this study analyses, in depth and for the first time, an entire non-English speaking European country (Spain), with complex academic web behaviour, which helps to better explain previous web mention results.Ortega, JL.; Orduña Malea, E.; Aguillo, IF. (2014). Are web mentions accurate substitutes for inlinks for Spanish universities?. Online Information Review. 38(1):59-77. doi:10.1108/OIR-10-2012-0189S5977381Adecannby, J. (2011), “Web link analysis of interrelationship between top ten African universities and world universities”, Annals of Library and Information Studies, Vol. 58 No. 2, pp. 128-138.Aguillo, I. (2009). Measuring the institution’s footprint in the web. Library Hi Tech, 27(4), 540-556. doi:10.1108/073788309Aguillo, I.F. , Ortega, J.L. and Fernández, M. (2008), “Webometric ranking of world universities: introduction, methodology, and future developments”, Higher Education in Europe, Vol. 33 Nos 2/3, pp. 234-244.Aguillo, I. F., Granadino, B., Ortega, J. L., & Prieto, J. A. (2006). Scientific research activity and communication measured with cybermetrics indicators. Journal of the American Society for Information Science and Technology, 57(10), 1296-1302. doi:10.1002/asi.20433Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509Bar-Ilan, J. (2005). The use of web search engines in information science research. Annual Review of Information Science and Technology, 38(1), 231-288. doi:10.1002/aris.1440380106Bar-Ilan, J. (2004). A microscopic link analysis of academic institutions within a country - the case of Israel. Scientometrics, 59(3), 391-403. doi:10.1023/b:scie.0000018540.33706.c1Bar-Ilan, J. (2005). What do we know about links and linking? A framework for studying links in academic environments. Information Processing & Management, 41(4), 973-986. doi:10.1016/j.ipm.2004.02.005Björneborn, L., & Ingwersen, P. (2004). Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14), 1216-1227. doi:10.1002/asi.20077Bland, J.M. and Altman, D.G. (1996), “Transforming data”, British Medical Journal, Vol. 312 No. 7033, p.Cronin, B., Snyder, H. W., Rosenbaum, H., Martinson, A., & Callahan, E. (1998). Invoked on the Web. Journal of the American Society for Information Science, 49(14), 1319-1328. doi:10.1002/(sici)1097-4571(1998)49:143.0.co;2-wFriedman, M. (1937). The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance. Journal of the American Statistical Association, 32(200), 675-701. doi:10.1080/01621459.1937.10503522Harries, G., Wilkinson, D., Price, L., Fairclough, R., & Thelwall, M. (2004). Hyperlinks as a data source for science mapping. Journal of Information Science, 30(5), 436-447. doi:10.1177/0165551504046736Heimeriks, G. and Van den Besselaar, P. (2006), “Analyzing hyperlink networks: the meaning of hyperlink based indicators of knowledge”, Cybermetrics, Vol. 10, available at: http://cybermetrics.cindoc.csic.es/articles/v10i1p1.pdf (accessed 10 July 2013).Heimeriks, G., Hörlesberger, M., & Van den Besselaar, P. (2003). Scientometrics, 58(2), 391-413. doi:10.1023/a:1026296812830Kousha, K. and Horri, A. (2004), “The relationship between scholarly publishing and the counts of academic inlinks to Iranian university web sites: exploring academic link creation motivations”, Journal of Information Management and Scientometrics, Vol. 1 No. 2, pp. 13-22.Kousha, K., & Thelwall, M. (2009). Google book search: Citation analysis for social science and the humanities. Journal of the American Society for Information Science and Technology, 60(8), 1537-1549. doi:10.1002/asi.21085Kretschmer, H., & Aguillo, I. F. (2004). Visibility of collaboration on the Web. Scientometrics, 61(3), 405-426. doi:10.1023/b:scie.0000045118.68430.fdOrduña-Malea, E. (2012), “Fuentes de enlaces web para análisis cibermétricos (2012)”, Anuario Thinkepi, Vol. 6 No. 1, pp. 276-280.Orduña-Malea, E. (2013), “Espacio universitario español en la Web (2010): estudio descriptivo de instituciones y productos académicos a través del análisis de subdominios y subdirectorios”, Revista Española de Documentación Científica, Vol. 36 No. 3.Orduña-Malea, E., & Ontalba-Ruipérez, J.-A. (2012). Proposal for a multilevel university cybermetric analysis model. Scientometrics, 95(3), 863-884. doi:10.1007/s11192-012-0868-5Orduña-Malea, E., Serrano-Cobos, J., Ontalba-Ruipérez, J. A., & Lloret-Romero, N. (2010). Presencia y visibilidad web de las universidades públicas españolas. Revista española de Documentación Científica, 33(2), 246-278. doi:10.3989/redc.2010.2.740Ortega, J. L., & Aguillo, I. F. (2008). Visualization of the Nordic academic web: Link analysis using social network tools. Information Processing & Management, 44(4), 1624-1633. doi:10.1016/j.ipm.2007.09.010Ortega, J. L., & Aguillo, I. F. (2009). Análisis estructural de la web académica iberoamericana. Revista española de Documentación Científica, 32(3), 51-65. doi:10.3989/redc.2009.3.689Ortega, J. L., Aguillo, I., Cothey, V., & Scharnhorst, A. (2007). Maps of the academic web in the European Higher Education Area — an exploration of visual web indicators. Scientometrics, 74(2), 295-308. doi:10.1007/s11192-008-0218-9Qiu, J., Chen, J., & Wang, Z. (2004). An analysis of backlink counts and Web Impact Factorsfor Chinese university websites. Scientometrics, 60(3), 463-473. doi:10.1023/b:scie.0000034387.76981.83Seeber, M., Lepori, B., Lomi, A., Aguillo, I., & Barberio, V. (2012). Factors affecting web links between European higher education institutions. Journal of Informetrics, 6(3), 435-447. doi:10.1016/j.joi.2012.03.001Seidman, E. (2007), “We are flattered, but …”, Bing Community, available at: www.bing.com/community/site_blogs/b/search/archive/2007/03/28/we-are-flattered-but.aspx (accessed 20 October 2012).Smith, A.G. (1999), “A tale of two web spaces: comparing sites using web impact factors”, Journal of Documentation, Vol. 55 No. 5, pp. 577-592.Smith, A., & Thelwall, M. (2002). Scientometrics, 54(3), 363-380. doi:10.1023/a:1016030415822Stuart, D., & Thelwall, M. (2006). Investigating triple helix relationships using URL citations: a case study of the UK West Midlands automobile industry. Research Evaluation, 15(2), 97-106. doi:10.3152/147154406781775968Thelwall, M. (2001). Extracting macroscopic information from Web links. Journal of the American Society for Information Science and Technology, 52(13), 1157-1168. doi:10.1002/asi.1182Thelwall, M. (2002). An initial exploration of the link relationship between UK university Web sites. Aslib Proceedings, 54(2), 118-126. doi:10.1108/00012530210435248Thelwall, M. and Aguillo, I.F. (2003), “La salud de las web universitarias españolas”, Revista Española de Documentación Científica, Vol. 26 No. 3, pp. 291-305.Thelwall, M., & Kousha, K. (2008). Online presentations as a source of scientific impact? An analysis of PowerPoint files citing academic journals. Journal of the American Society for Information Science and Technology, 59(5), 805-815. doi:10.1002/asi.20803Thelwall, M., & Sud, P. (2011). A comparison of methods for collecting web citation data for academic organizations. Journal of the American Society for Information Science and Technology, 62(8), 1488-1497. doi:10.1002/asi.21571Thelwall, M., & Sud, P. (2012). Webometric research with the Bing Search API 2.0. Journal of Informetrics, 6(1), 44-52. doi:10.1016/j.joi.2011.10.002Thelwall, M., & Zuccala, A. (2008). A university-centred European Union link analysis. Scientometrics, 75(3), 407-420. doi:10.1007/s11192-007-1831-8Thelwall, M., Tang, R., & Price, L. (2003). Scientometrics, 56(3), 417-432. doi:10.1023/a:1022387105904Thelwall, M., Binns, R., Harries, G., Page-Kennedy, T., Price, L., & Wilkinson, D. (2002). Scientometrics, 53(1), 95-111. doi:10.1023/a:1014836021080Vaughan, L. (2012). An Alternative Data Source for Web Hyperlink Analysis: «Sites Linking In» at Alexa Internet. Collnet Journal of Scientometrics and Information Management, 6(1), 31-42. doi:10.1080/09737766.2012.10700922Vaughan, L., & Romero-Frías, E. (2012). Exploring Web keyword analysis as an alternative to link analysis: a multi-industry case. Scientometrics, 93(1), 217-232. doi:10.1007/s11192-012-0640-xVaughan, L., & Shaw, D. (2003). Bibliographic and Web citations: What is the difference? Journal of the American Society for Information Science and Technology, 54(14), 1313-1322. doi:10.1002/asi.10338Vaughan, L., & Yang, R. (2012). Web data as academic and business quality estimates: A comparison of three data sources. Journal of the American Society for Information Science and Technology, 63(10), 1960-1972. doi:10.1002/asi.22659Vaughan, L., & You, J. (2010). Word co-occurrences on Webpages as a measure of the relatedness of organizations: A new Webometrics concept. Journal of Informetrics, 4(4), 483-491. doi:10.1016/j.joi.2010.04.005Vaughan, L., Kipp, M. E. I., & Gao, Y. (2007). Why are Websites co-linked? The case of Canadian universities. Scientometrics, 72(1), 81-92. doi:10.1007/s11192-007-1707-y(The) Washington Post(2009), “It's official: Yahoo-Microsoft announce ten-year search/ad pact”, The Washington Post, available at: www.washingtonpost.com/wp-dyn/content/article/2009/07/29/AR2009072901108.html (accessed 27 February 2013).Wilkinson, D., Harries, G., Thelwall, M., & Price, L. (2003). Motivations for academic web site interlinking: evidence for the Web as a novel source of information on informal scholarly communication. Journal of Information Science, 29(1), 49-56. doi:10.1177/016555150302900105Zhang, Y. (2006). The Effect of Open Access on Citation Impact: A Comparison Study Based on Web Citation Analysis. Libri, 56(3). doi:10.1515/libr.2006.14

Mobile Web Adoption in Top Ranked University Libraries: A Preliminary Study

This paper aims to study the level of adoption of mobile access to the academic libraries in the best universities in the world as well as the quality of services offered in order to ascertain if the quality of academic apps and mobile websites are at the level of the overall web impact of world-class universities. For the top 50 universities according to the Ranking Web of Universities (2014), we determined whether there is a mobile website or app for their libraries. Finally we evaluated the services offered against a list of 14 indicators. The results show that 88% of the libraries studied (44) offer mobile access via web or app, showing a high level of mobile adoption in elite universities. The form is clearly uneven: 80% (40) offers mobile web access while only 34% (17) has an app. As to the content, no library offered all 14 points evaluated, and the results are varied. Only 50% of apps meet at least half the indicators. In the case of mobile web this figure improves notably to 74.3%. We can note a high level of mobile web adoption in the world's best universities, although the quality does not reach their level of excellence. (C) 2016 Elsevier Inc. All rights reserved.Torres-Pérez, P.; Méndez-Rodríguez, E.; Orduña Malea, E. (2016). Mobile Web Adoption in Top Ranked University Libraries: A Preliminary Study. Journal of Academic Librarianship. 42(4):329-339. doi:10.1016/j.acalib.2016.05.011S32933942

H Index Scholar: the h-index for Spanish public universities' professors of humanities and social sciences

[EN] The H-Index Scholar is a bibliometric index that measures the productivity and scientific impact of the academic production in humanities and social sciences by professors and researchers at public Spanish universities. The methodology consisted of counting their publications and citations received in Google Scholar. The main features and characteristics of the index are explained. Despite technical and methodological problems that Google Scholar might have as a source of information, the authors estimate that they do not affect substantially the calculated h and g indexes, probably being the error lower than 10%. The total population analyzed was 40,993 researchers, but data are displayed only for 13,518 researchers, the ones located in the first tertile of their respective areas.[ES] H Index Scholar es un índice bibliométrico sobre la productividad e impacto científico de la producción académica de los profesores e investigadores de universidades públicas españolas en humanidades y ciencias sociales. Se realiza mediante el recuento de sus publicaciones y de las citas bibliográficas que han recibido en Google Scholar. Se describen las principales funciones y características del producto. A pesar de los problemas técnicos y metodológicos que pueda presentar Google Scholar como fuente de información, los autores estiman que no afectan en lo sustancial a los índices h y g ofrecidos, estando dentro de una tasa de error del 10%. La población total analizada ha sido de 40.993 profesores, de los que se visualiza un total de 13.518 situados en el primer tercil de sus respectivas áreas.Trabajo financiado con cargo al proyecto HAR2011-30383-C02-02 de la Dirección General de Investigación y Gestión del Plan Nacional de I+D+I. Ministerio de Economía y Competitividad.Delgado López, E.; Orduña Malea, E.; Jimenez Contreras, E.; Ruiz Pérez, R. (2014). H Index Scholar: el índice H de los profesores de las universidades públicas españolas en humanidades y ciencias sociales. El Profesional de la Información. 23(1):87-94. https://doi.org/10.3145/epi.2014.ene.11S8794231Aguillo, I. F., Ortega, J. L., Fernández, M., & Utrilla, A. M. (2010). Indicators for a webometric ranking of open access repositories. Scientometrics, 82(3), 477-486. doi:10.1007/s11192-010-0183-yArchambault, Eric; Larivière, Vincent (2010). "The limits of bibliometrics for the analysis of the social sciences and humanities literature". World social science report: competing in the knowledge society. Unesco, pp. 251-254.Archambault, É., Vignola-Gagné, É., Côté, G., Larivière, V., & Gingrasb, Y. (2006). Benchmarking scientific output in the social sciences and humanities: The limits of existing databases. Scientometrics, 68(3), 329-342. doi:10.1007/s11192-006-0115-zArdanuy, J. (2013). Sixty years of citation analysis studies in the humanities (1951-2010). Journal of the American Society for Information Science and Technology, 64(8), 1751-1755. doi:10.1002/asi.22835Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131-152. doi:10.1007/s11192-006-0144-7Giménez-Toledo, E., & Román-Román, A. (2009). Assessment of humanities and social sciences monographs through their publishers: a review and a study towards a model of evaluation. Research Evaluation, 18(3), 201-213. doi:10.3152/095820209x471986Gorraiz, J., Purnell, P. J., & Glänzel, W. (2013). Opportunities for and limitations of the Book Citation Index. Journal of the American Society for Information Science and Technology, 64(7), 1388-1398. doi:10.1002/asi.22875Hicks, Diana M.; Wang, Jian (2009). "Towards a bibliometric database for the social sciences and humanities" [report]. http://works.bepress.com/diana_hicks/18Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569-16572. doi:10.1073/pnas.0507655102Jacsó, P. (2008). Google Scholar revisited. Online Information Review, 32(1), 102-114. doi:10.1108/14684520810866010Jacso´, P. (2008). The pros and cons of computing the h‐index using Google Scholar. Online Information Review, 32(3), 437-452. doi:10.1108/14684520810889718Jacsó, P. (2012). Using Google Scholar for journal impact factors and the h‐index in nationwide publishing assessments in academia – siren songs and air‐raid sirens. Online Information Review, 36(3), 462-478. doi:10.1108/14684521211241503Kousha, K., & Thelwall, M. (2007). Google Scholar citations and Google Web/URL citations: A multi-discipline exploratory analysis. Journal of the American Society for Information Science and Technology, 58(7), 1055-1065. doi:10.1002/asi.20584Kousha, K., & Thelwall, M. (2007). Sources of Google Scholar citations outside the Science Citation Index: A comparison between four science disciplines. Scientometrics, 74(2), 273-294. doi:10.1007/s11192-008-0217-xKousha, K., Thelwall, M., & Rezaie, S. (2011). Assessing the citation impact of books: The role of Google Books, Google Scholar, and Scopus. Journal of the American Society for Information Science and Technology, 62(11), 2147-2164. doi:10.1002/asi.21608Leydesdorff, L., & Felt, U. (2012). Edited volumes, monographs and book chapters in the Book Citation Index (BKCI) and Science Citation Index (SCI, SoSCI, A&HCI). Journal of Scientometric Research, 1(1), 28-34. doi:10.5530/jscires.2012.1.7Nederhof, A. J. (2006). Bibliometric monitoring of research performance in the Social Sciences and the Humanities: A Review. Scientometrics, 66(1), 81-100. doi:10.1007/s11192-006-0007-2Orduña-Malea, Enrique (2012). Propuesta de un modelo de análisis redinformétrico multinivel para el estudio sistémico de las universidades españolas. Valencia: Universidad Politécnica de Valencia [tesis doctoral]Orduña-Malea, E., & Ontalba-Ruipérez, J.-A. (2012). Proposal for a multilevel university cybermetric analysis model. Scientometrics, 95(3), 863-884. doi:10.1007/s11192-012-0868-5Orduña-Malea, E., Serrano-Cobos, J., & Lloret-Romero, N. (2009). Las universidades públicas españolas en Google Scholar: presencia y evolución de su publicación académica web. El Profesional de la Informacion, 18(5), 493-500. doi:10.3145/epi.2009.sep.02Thelwall, M. (2002). Research dissemination and invocation on the Web. Online Information Review, 26(6), 413-420. doi:10.1108/14684520210452745Torres-Salinas, D., Ruiz-Pérez, R., & Delgado-López-Cózar, E. (2009). Google Scholar como herramienta para la evaluación científica. El Profesional de la Informacion, 18(5), 501-510. doi:10.3145/epi.2009.sep.03White, H. D., Boell, S. K., Yu, H., Davis, M., Wilson, C. S., & Cole, F. T. H. (2009). Libcitations: A measure for comparative assessment of book publications in the humanities and social sciences. Journal of the American Society for Information Science and Technology, 60(6), 1083-1096. doi:10.1002/asi.2104

Identifying institutional relationships in a geographically distributed public health system using interlinking and co-authorship methods

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s11192-016-1839-zLink analysis is highly effective in detecting relationships between different institutions, relationships that are stronger the greater their geographical proximity. We therefore decided to apply an interlinking analysis to a set of geographically dispersed research entities and to compare the results with the co-authorship patterns between these institutions in order to determine how, and if, these two techniques might reveal complementary insights. We set out to study the specific sector of public health in Spain, a country with a high degree of regional autonomy. We recorded all Spanish health entities (and their corresponding URLs) that belong to, and were hyperlinked from, the national government or any of the regional governments, gathering a total of 263 URLs. After considering their suitability for web metric analysis, interlinking scores between all valid URLs were obtained. In addition, the number of co-authored articles by each pair of institutions and the total scientific output per institution were retrieved from Scopus. Both interlinking and co-authorship methods detect the existence of strength subnets of geographically distributed nodes (especially the Catalan entities) as well as their high connectivity with the main national network nodes (subnet of nodes distributed according to dependence on national government, in this case Spain). However, the resulting interlinking pattern shows a low but significant correlation (r = 0.5) with scientific co-authorship patterns. The existence of institutions that are strongly interlinked but with limited scientific collaboration (and vice versa) reveals that links within this network are not accurately reflecting existing scientific collaborations, due to inconsistent web content development.Ontalba Ruipérez, JA.; Orduña Malea, E.; Alonso-Arroyo, A. (2016). Identifying institutional relationships in a geographically distributed public health system using interlinking and co-authorship methods. Scientometrics. 106(3):1167-1191. doi:10.1007/s11192-016-1839-zS116711911063Aguillo, I. F., Granadino, B., Ortega, J. L., & Prieto, J. A. (2006). Scientific research activity and communication measured with cybermetrics indicators. Journal of the American Society for Information Science and Technology, 57(10), 1296–1302.Almind, T. C., & Ingwersen, P. (1998). Informetric analyses on the world wide web: methodological approaches to ‘webometrics’. Journal of Documentation, 53(4), 404–426.Barabasi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.Bar-Ilan, J. (2005). What do we know about links and linking? A framework for studying links in academic environments. Information Processing and Management, 41(4), 973–986.Barnett, George A., & Park, Han W. (2014). Examining the international internet using multiple measures: New methods for measuring the communication base of globalized cyberspace. Quality and Quantity, 48(1), 563–575.Eurostat. (2011). Regions in the European Union. Nomenclature of territorial units for statistics. NUTS 2010/EU-27. http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-RA-11-011/EN/KS-RA-11-011-EN.PDF Accessed 16 August 2015.García-Lacalle, J., Pina, V., & Royo, S. (2011). The unpromising quality and evolution of Spanish public hospital web sites. Online Information Review, 35(1), 86–112.García-Santiago, L., & Moya-Anegón, F. (2009). Using co-outlinks to mine heterogeneous networks. Scientometrics, 79(3), 681–702.González-Bailón, S. (2009). Opening the black box of link formation: Social factors underlying the structure of the web. Social Networks, 31(2009), 271–280.Heimeriks, G., Hörlesberger, M., & Van den Besselaar, P. (2003). Mapping communication and collaboration in heterogeneous research networks. Scientometrics, 58(2), 391–413.Heimeriks, G., & Van den Besselaar, P. (2006). Analyzing hyperlinks networks: The meaning of hyperlink based indicators of knowledge production. Cybermetrics, 10(1), http://cybermetrics.cindoc.csic.es/articles/v10i1p1.pdf . Accessed 16 August 2015.Holmberg, K. (2010). Co-inlinking to a municipal Web space: A webometric and content analysis. Scientometrics, 83(3), 851–862.Holmberg, K., & Thelwall, M. (2009). Local government web sites in Finland: A geographic and webometric analysis. Scientometrics, 79(1), 157–169.Khan, G. F., & Park, H. W. (2011). Measuring the triple helix on the web: Longitudinal trends in the university-industry-government relationship in Korea. Journal of the American Society for Information Science and Technology, 62(12), 2443–2455.Lang, P. B., Gouveia, F. C., & Leta, J. (2014). Health research networks on the web: An analysis of the Brazilian presence. Cadernos de Saúde Pública, 30(2), 369–378.Leydesdorff, L., & Curran, M. (2000). Mapping university-industry-government relations on the Internet: The construction of indicators for a knowledge-based economy. Cybermetrics, 4(1). http://www.cybermetrics.info/articles/v4i1p2.pdf . Accessed 16 August 2015.Méndez-Vásquez, R. I., Suñen-Pinyol, E., Cervelló, R., & Camí, J. (2008). Mapa bibliométrico de España 1996–2004: Biomedicina y ciencias de la salud. Medicina clínica, 130(7), 246–253.Méndez-Vásquez, R. I., Suñén-Pinyol, E., & Rovira, L. (2012). Caracterización bibliométrica de la investigación biomédica española, WOS 1997–2011. http://bac.fundaciorecerca.cat/mb11 . Accessed 16 August 2015.Ministerio de Sanidad, Servicios Sociales e Igualdad. (2012). Sistema Nacional de Salud. España 2012. http://www.msssi.gob.es/organizacion/sns/docs/sns2012/SNS012__Espanol.pdf . Accessed 16 August 2015.Orduna-Malea, E., Ortega, J. L., & Aguillo, I. F. (2014). Influence of language and file type on the web visibility of top European universities. Aslib Proceedings, 66(1), 96–116.Orduna-Malea, E., & Aguillo, I. F. (2014). Cibermetría. Midiendo el espacio red. Barcelona: UOC Publishing.Orduna-Malea, E., & Aytac, S. (2015). Revealing the online network between university and industry: The case of Turkey. Scientometrics, 105(3), 1849–1866.Orduna-Malea, E., Delgado López-Cózar, E., Serrano-Cobos, J., & Romero, N. L. (2015a). Disclosing the network structure of private companies on the web: The case of Spanish IBEX 35 share index. Online Information Review, 39(3), 360–382.Orduna-Malea, E., & Ontalba-Ruipérez, J. A. (2013). Proposal for a multilevel university cybermetric analysis model. Scientometrics, 95(3), 863–884.Orduna-Malea, E., Torres-Salinas, D., & Delgado López-Cózar, E. (2015b). Hyperlinks embedded in twitter as a proxy for total external in-links to international university websites. Journal of the Association for Information Science and Technology, 66(7), 1447–1462.Ortega, J. L. (2007). Visualización de la Web universitaria Europea: análisis cuantitativo de enlaces a través de técnicas cibermétricas. Madrid: Universidad Carlos III de Madrid.Ortega, J. L., & Aguillo, I. F. (2009). Mapping world-class universities on the web. Information Processing and Management, 45(2), 272–279.Ortega, J. L., Orduna-Malea, E., & Aguillo, I. F. (2014). Are web mentions accurate substitutes for inlinks for Spanish universities? Online Information Review, 38(1), 59–77.Park, H. W. (2011). How do social scientists use link data from search engines to understand Internet-based political and electoral communication? Quality and Quantity, 46(2), 679–693.Park, H. W., & Thelwall, M. (2003). Hyperlink analyses of the World Wide Web: A review. Journal of Computer-Mediated Communication. doi: 10.1111/j.1083-6101.2003.tb00223.x .Romero-Frías, E., & Vaughan, L. (2010a). Patterns of web linking to heterogeneous groups of companies: The case of stock exchange indexes. Aslib Proceedings, 62(2), 144–164.Romero-Frías, E., & Vaughan, L. (2010b). European political trends viewed through patterns of Web linking. Journal of the American Society for Information Science and Technology, 61(10), 2109–2121.Seeber, M., Lepori, B., Lomi, A., Aguillo, I. F., & Barberio, V. (2012). Factors affecting web links between European higher education institutions. Journal of Informetrics, 6(3), 435–447.Stuart, D., & Thelwall, M. (2006). Investigating triple helix relationships using URL citations: A case study of the UK West Midlands automobile industry. Research Evaluation, 15(2), 97–106.Sud, P., & Thelwall, M. (2014). Linked title mentions: A new automated link search candidate. Scientometrics, 101(3), 1831–1849.Thelwall, M. (2001). Extracting macroscopic information from web links. Journal of the American Society for Information Science and Technology, 52(13), 1157–1168.Thelwall, M. (2002). Evidence for the existence of geographic trends in university web site interlinking. Journal of Documentation, 58(5), 563–574.Thelwall, M. (2004). Link analysis: An information science approach. San Diego: Elsevier.Thelwall, M. (2006). Interpreting social science link analysis research: A theoretical framework. Journal of the American Society for Information Science and Technology, 57(1), 60–68.Thelwall, M. (2009). Introduction to webometrics: Quantitative web research for the social sciences. San Rafael, CA: Morgan & Claypool Publishers.Thelwall, M., & Sud, P. (2011). A comparison of methods for collecting web citation data for academic organisations. Journal of the American Society for Information Science and Technology, 62(8), 1488–1497.Thelwall, M., & Tang, R. (2003). Disciplinary and linguistic considerations for academic web linking: An exploratory hyperlink mediated study with Mainland China and Taiwan. Scientometrics, 58(1), 155–181.Thelwall, M., Tang, R., & Price, L. (2003). Linguistic patterns of Academic web use in Western Europe. Scientometrics, 56(3), 417–432.Vaughan, L. (2006). Visualizing linguistic and cultural differences using web co-link data. Journal of the American Society for Information Science and Technology, 57(9), 1178–1193.Vaughan, L., & Thelwall, M. (2003). Scholarly use of the web: What are the key inducers of links to journal web sites? Journal of the American Society for Information Science and Technology, 54(1), 29–38.Vaughan, L., & Thelwall, M. (2004). Search engine coverage bias: Evidence and possible causes. Information Processing and Management, 40(4), 693–707.Vaughan, L., & Wu, G. (2004). Links to commercial websites as a source of business information. Scientometrics, 60(3), 487–496.Vaughan, L., & You, J. (2006). Comparing business competition positions based on Web co-link data: The global market vs. the Chinese market. Scientometrics, 68(3), 611–628.Weber, M. S., & Monge, P. (2011). The flow of digital news in a network of sources, authorities, and hubs. Journal of Communication, 61(6), 1062–1081.Wilkinson, D., Harries, G., Thelwall, M., & Price, L. (2003). Motivations for academic Web site interlinking: Evidence for the Web as a novel source of information on informal scholarly communication. Journal of information science, 29(1), 49–56.Wilkinson, D., & Thelwall, M. (2013). Search markets and search results: The case of Bing. Library and Information Science Research, 35(4), 318–325

Análisis y evaluación de la calidad del sitio web de la Universidad del Azuay

[ES] Cada día las universidades se preocupan por analizar y evaluar la calidad de sus sitios web debido a los beneficios que pueden obtener. Un sitio web atractivo, fácil de usar y que permita transmitir la información que la institución considere necesario a su público de interés es fundamental para la generación de prestigio, tener visibilidad, atraer potenciales estudiantes, colaboradores, etc., y ante esta necesidad se justifica la creación de un modelo conceptual de evaluación de calidad orientado a la visibilidad, proponiendo el diseño de un modelo específico. Como estrategia se propone crear un modelo que evalúa tres criterios principales que son Usabilidad, Visibilidad y Tráfico, cada criterio tiene categorías, subcategorías e indicadores que permiten evaluar estos criterios. Con el fin de testear este modelo se aplica a una universidad real como es la Universidad del Azuay ubicada en Cuenca (Ecuador). Se obtienen los primeros resultados observando que es adecuada en temas de navegación, velocidad, se detecta también que existen algunos aspectos mejorables en temas de accesibilidad, atención al usuario, interfaz, redes sociales como es el caso de YouTube y LinkedIn, tráfico como el Trust Flow en el que se observa que el porcentaje es bajo, entre otros. Por ello, se proponen mejoras que se podrían implementar en el futuro en caso de que la institución lo considere necesario para lo cual se realiza una pequeña comparativa con dos sitios web de universidades internacionales como lo es la Universidad de Harvard y la Universidad Politécnica de Valencia.[EN] Every day the universities are concerned for analyzing and evaluating the quality of their websites for the benefits they can obtain. An attractive website, easy to use and that allows transmitting the information that the institution considers necessary to the public of interest is fundamental for the generation of prestige, visibility, to attract potential students, collaborators, etc. This need justified the creation of a conceptual model of quality evaluation oriented to visibility, proposing the design of a specific model. As a strategy, it is proposed to create a model that evaluates three main criteria that are Usability, Visibility and Traffic; each criterion has categories, sub-categories and indicators that allow evaluating these criteria. For testing this model is applied to a real university such as the University of Azuay located in Cuenca (Ecuador). The first results are obtained observing that it is good in navigation, speed. In this model is detected that there are some aspects that can be improved in accessibility, user attention, interface, social networks such as YouTube and LinkedIn, traffic as the Trust Flow in which it is observed that the percentage is low, and others. For this reason, in the model there are improvements that could be implemented in the future if the institution considere necessary. The comparison is made with two websites of international universities.Guamán Barbecho, EP. (2019). Análisis y evaluación de la calidad del sitio web de la Universidad del Azuay. http://hdl.handle.net/10251/125999TFG