Genesis of Altmetrics or Article-level Metrics for Measuring Efficacy of Scholarly Communications: Current Perspectives

The article-level metrics (ALMs) or altmetrics becomes a new trendsetter in recent times for measuring the impact of scientific publications and their social outreach to intended audiences. The popular social networks such as Facebook, Twitter, and Linkedin and social bookmarks such as Mendeley and CiteULike are nowadays widely used for communicating research to larger transnational audiences. In 2012, the San Francisco Declaration on Research Assessment got signed by the scientific and researchers communities across the world. This declaration has given preference to the ALM or altmetrics over traditional but faulty journal impact factor (JIF)-based assessment of career scientists. JIF does not consider impact or influence beyond citations count as this count reflected only through Thomson Reuters' Web of Science database. Furthermore, JIF provides indicator related to the journal, but not related to a published paper. Thus, altmetrics now becomes an alternative metrics for performance assessment of individual scientists and their contributed scholarly publications. This paper provides a glimpse of genesis of altmetrics in measuring efficacy of scholarly communications and highlights available altmetric tools and social platforms linking altmetric tools, which are widely used in deriving altmetric scores of scholarly publications. The paper thus argues for institutions and policy makers to pay more attention to altmetrics based indicators for evaluation purpose but cautions that proper safeguards and validations are needed before their adoption

Scientific Output from Latin America and the Caribbean – Identification of the Main Institutions for Regional Open Access Integration Strategies

Latin America is a region in which two thirds of the investment in research and development are funded by State resources. It can be foreseen that in the near future governments in the region will encourage and promote, or require by law or mandates, that scientific output from the region become visible and accessible in open access repositories and portals. This paper presents the results of a survey to identify the institutions of the region with the largest volume of scientific output and most exposure of their output on the Web, in order to help make those institutions visible to national, regional and international organizations involved in open access strategies and programs in Latin America and the Caribbean. The results show a leading position by universities from Brazil; a strong presence of universities from Mexico, Colombia, Argentina, Chile and Venezuela, and some presence of universities from Ecuador, Peru, Costa Rica, Cuba, Puerto Rico and Urugua

Utilising content marketing metrics and social networks for academic visibility

There are numerous assumptions on research evaluation in terms of quality and relevance of academic contributions. Researchers are becoming increasingly acquainted with bibliometric indicators, including; citation analysis, impact factor, h-index, webometrics and academic social networking sites. In this light, this chapter presents a review of these concepts as it considers relevant theoretical underpinnings that are related to the content marketing of scholars. Therefore, this contribution critically evaluates previous papers that revolve on the subject of academic reputation as it deliberates on the individual researchers’ personal branding. It also explains how metrics are currently being used to rank the academic standing of journals as well as higher educational institutions. In a nutshell, this chapter implies that the scholarly impact depends on a number of factors including accessibility of publications, peer review of academic work as well as social networking among scholars.peer-reviewe

Measuring the Institution's Footprint in the Web

Purpose: Our purpose is to provide an alternative, although complementary, system for the evaluation of the scholarly activities of academic organizations, scholars and researchers, based on web indicators, in order to speed up the change of paradigm in scholarly communication towards a new fully electronic 21st century model. Design/methodology/approach: In order to achieve these goals, a new set of web indicators has been introduced, obtained mainly from data gathered from search engines, the new mediators of scholarly communication. We found that three large groups of indicators are feasible to obtain and relevant for evaluation purposes: activity (web publication); impact (visibility) and usage (visits and visitors). Findings: As a proof of concept, a Ranking Web of Universities has been built with Webometrics data. There are two relevant findings: ranking results are similar to those obtained by other bibliometric-based rankings; and there is a concerning digital divide between North American and European universities, which appear in lower positions when compared with their US & Canada counterparts. Research limitations / implications: Cybermetrics is still an emerging discipline so new developments should be expected when more empirical data become available. Practical implications: The proposed approach suggests the publication of truly electronic journals, rather than digital versions of printed articles. Additional materials such as raw data and multimedia files should be included along with other relevant information arising from more informal activities. These repositories should be Open Access, available as part of the public Web, indexed by the main commercial search engines. We anticipate that these actions could generate larger Web-based audiences, reduce the costs of publication and access and allow third parties to take advantage of the knowledge generated, without sacrificing peer review, which should be extended (pre- & post-) & expanded (closed & open). Originality / value: A full taxonomy of web indicators is introduced for describing and evaluating research activities, academic organizations and individual scholars and scientists. Previous attempts for building such classification were more incomplete and not taking into account feasibility and efficiency

The importance of research in university's webometric ranking: UNIOSUN case study

Objective: Cybermetrics or webometrics is an emerging discipline concerned with the quantitative analysis of the internet and web contents related to ranking of the World Universities which from an academic and scientific point of view are very important and informative. The aim of the study is to elucidate the role of research in the webometric ranking of Universities.Methods: A review of literature was conducted.Results: Websites are the most efficient and cheapest way for boosting all the three academic missions: teaching, research and technology transfer. Web indicators are used for ranking purposes; they are not based on number of visits or page design but on the global performance and visibility of the universities. The current composite indicator include impact variable (50%) based on link visibility of the University and web activity (50%) on a ratio 1:1. The activity variable comprises of web presence, openness and excellence. Clearly, the research mission plays a central role in the definition of World-class university status; academic papers published in high impact international journals are very important in the ranking. Many indicators serve the purpose of ranking, but most observers know that research matters more than anything else in defining the best institutions.Conclusion: A large web presence is made possible only with the effort of a large group of authors. All academic staff should be involved in quality research activities. Availability of infrastructure, scientific collaborations at all levels are most important in increasing the capacity of scientific productivity and visibility which are the major components in ranking.Keywords: Research, role, webometrics, UNIOSUN, universitie

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