The role of ego in academic profile services: comparing Google scholar, ResearchGate, Mendeley, and ResearcherID

Academic profiling services are a pervasive feature of scholarly life. Alberto Martín-Martín, Enrique Orduna-Malea and Emilio Delgado López-Cózar discuss the advantages and disadvantages of major profile platforms and look at the role of ego in how these services are built and used. Scholars validate these services by using them and should be aware that the portraits shown in these platforms depend to a great extent on the characteristics of the “mirrors” themselves

Google Scholar and the gray literature: A reply to Bonato’s review

Version 1.0, Published on 11 February 2017, GranadaThis work has been rejected in the Journal of the Medical Library Association (JMLA), both the full version (24th December, 2016) and a letter to editor version (31st January, 2017).Recently, a review concluded that Google Scholar (GS) is not a suitable source of information “for identifying recent conference papers or other gray literature publications”. The goal of this letter is to demonstrate that GS can be an effective tool to search and find gray literature, as long as appropriate search strategies are used. To do this, we took as examples the same two case studies used by the original review, describing first how GS processes original’s search strategies, then proposing alternative search strategies, and finally generalizing each case study to compose a general search procedure aimed at finding gray literature in Google Scholar for two wide selected case studies: a) all contributions belonging to a congress (the ASCO Annual Meeting); and b) indexed guidelines as well as gray literature within medical institutions (National Institutes of Health) and governmental agencies (U.S. Department of Health & Human Services). The results confirm that original search strategies were undertrained offering misleading results and erroneous conclusions. Google Scholar lacks many of the advanced search features available in other bibliographic databases (such as Pubmed), however, it is one thing to have a friendly search experience, and quite another to find gray literature. We finally conclude that Google Scholar is a powerful tool for searching gray literature, as long as the users are familiar with all the possibilities it offers as a search engine. Poorly formulated searches will undoubtedly return misleading results

Classic papers: déjà vu, a step further in the bibliometric exploitation of Google Scholar

After giving a brief overview of Eugene Garfield’s contributions to the issue of identifying and studying the most cited scientific articles, manifested in the creation of his Citation Classics, the main characteristics and features of Google Scholar’s new service -Classic Papers-, as well as its main strengths and weaknesses, are addressed. This product currently displays the most cited English-language original research articles by fields and published in 2006Alberto Martín-Martín enjoys a four-year doctoral fellowship (FPU2013/05863) granted by the Ministerio de Educación, Cultura, y Deportes (Spain). Enrique Orduña-Malea holds a Juan de la Cierva postdoctoral fellowship (IJCI-2015-26702) by the Ministerio de Economía y Competitividad (Spain)

The financial transmission of housing bubbles : evidence from Spain

¿Cuáles son los efectos de una burbuja inmobiliaria sobre el resto de la economía? En este trabajo mostramos que, si las empresas y los bancos están restringidos, una burbuja inmobiliaria inicialmente reduce el crédito a empresas no relacionadas con el sector inmobiliario. Esto es así porque el aumento inicial de la demanda de crédito de empresas relacionadas con la construcción no se ve reflejado en un aumento de la oferta de crédito por parte de los bancos. Sin embargo, a medida que la burbuja continúa, las empresas de construcción devuelven sus préstamos y aumenta el patrimonio de los bancos y, por lo tanto, se produce una expansión en la oferta de crédito a todas las empresas de la economía. De este modo, la reducción inicial de crédito en sectores no relacionados con la actividad inmobiliaria da paso a un aumento generalizado del crédito (y, por tanto, de la actividad) en toda la economía inducido por la burbuja inmobiliaria. Estas predicciones son confirmadas por la evidencia empírica a lo largo del reciente boom inmobiliario de la economía española. En los primeros años de la burbuja, las empresas no relacionadas con la vivienda redujeron su crédito procedente de los bancos más expuestos a la burbuja. En los últimos años, sin embargo, estas mismas empresas aumentaron su crédito procedente de esos mismos bancosWhat are the effects of a housing bubble on the rest of the economy? We show that if firms and banks face collateral constraints, a housing bubble initially raises credit demand by housing firms while leaving credit supply unaffected. It therefore crowds out credit to non-housing firms. If time passes and the bubble lasts, however, housing firms eventually pay back their higher loans. This leads to an increase in banks’ net worth and thus to an expansion in their supply of credit to all firms: crowding-out gives way to crowding-in. These predictions are confirmed by empirical evidence from the recent Spanish housing bubble. In the early years of the bubble, non-housing firms reduced their credit from banks that were more exposed to the bubble, and firms that were more exposed to these banks had lower credit and output growth. In its last years, these effects were reverse

Métricas en perfiles académicos: ¿un nuevo juego adictivo para los investigadores?

[EN] This study aims to promote reflection and bring attention to the potential adverse effects of academic social networks on science. These academic social networks, where authors can display their publications, have become new scientific communication channels, accelerating the dissemination of research results, facilitating data sharing, and strongly promoting scientific collaboration, all at no cost to the user. One of the features that make them extremely attractive to researchers is the possibility to browse through a wide variety of bibliometric indicators. Going beyond publication and citation counts, they also measure usage, participation in the platform, social connectivity, and scientific, academic and professional impact. Using these indicators they effectively create a digital image of researchers and their reputations. However, although academic social platforms are useful applications that can help improve scientific communication, they also hide a less positive side: they are highly addictive tools that might be abused. By gamifying scientific impact using techniques originally developed for videogames, these platforms may get users hooked on them, like addicted academics, transforming what should only be a means into an end in itself.[ES] Pretende este trabajo provocar la reflexión y alertar de los posibles peligros para la ciencia que encierran las nuevas redes sociales académicas que tanto éxito están teniendo en nuestros días. Las redes sociales académicas donde los autores pueden mostrar sus publicaciones se han convertido en nuevos canales de comunicación científica, pues agilizan la diseminación de los resultados de investigación, facilitan la compartición de datos y fomentan la colaboración científica de forma extensa sin coste alguno. Una de las novedades principales de estas plataformas, que es lo que las hace enormemente atractivas para los investigadores, consiste en la disponibilidad de una amplia batería de indicadores bibliométricos que van más allá del conteo de publicaciones y citas pues permiten medir el uso, la participación, la conectividad social y el impacto científico, académico y profesional. Sobre estos indicadores se está construyendo la propia imagen y reputación digital de los científicos. Pues bien, todos estos beneficios de las redes sociales académicas en la mejora de la comunicación científica esconden un lado no tan positivo para la ciencia. Se trata de herramientas muy peligrosas, que pueden convertirse en auténticas adicciones. Mediante la gamificación del impacto científico a través de persuasivas técnicas procedentes de los videojuegos, estas plataformas pueden hacer que los usuarios queden enganchados, como académicos adictos, convirtiendo lo que es un medio en un fin en sí mismo.Orduña Malea, E.; Martín-Martín, A.; Delgado López-Cózar, E. (2016). Metrics in academic profiles: a new addictive game for researchers?. Revista Española de Salud Pública. 90:1-5. http://hdl.handle.net/10251/113023S159

Google Scholar como una fuente de evaluación científica: una revisión bibliográfica sobre errores de la base de datos

[ES] Google Scholar es un motor de búsqueda académico y herramienta de descubrimiento lanzada por Google (ahora Alphabet) en noviembre de 2004. El hecho de que para cada registro bibliográfico se proporcione información acerca del número de citas recibidas por dicho registro desde el resto de registros indizados en el sistema (independientemente de su fuente) ha propiciado su utilización en análisis bibliométricos y en procesos de evaluación de la actividad académica, especialmente en Ciencias Sociales y Humanidades. No obstante, la existencia de errores, en ocasiones de gran magnitud, ha provocado su rechazo y crítica por una parte de la comunidad científica. Este trabajo pretende precisamente realizar una revisión bibliográfica exhaustiva de todos los estudios que de forma monográfica o colateral proporcionan alguna evidencia empírica sobre cuáles son los errores cometidos por Google Scholar (y productos derivados, como Google Scholar Metrics y Google Scholar Citations). Los resultados indican que el corpus bibliográfico dedicado a los errores en Google Scholar es todavía escaso (n= 49), excesivamente fragmentado, disperso, con resultados obtenidos sin metodologías sistemáticas y en unidades no comparables entre sí, por lo que su cuantificación y su efecto real no pueden ser caracterizados con precisión. Ciertas limitaciones del propio buscador (tiempo requerido de limpieza de datos, límite de citas por registro y resultados por consulta) podrían ser la causa de esta ausencia de trabajos empíricos.[EN] Google Scholar (GS) is an academic search engine and discovery tool launched by Google (now Alphabet) in November 2004. The fact that GS provides the number of citations received by each article from all other indexed articles (regardless of their source) has led to its use in bibliometric analysis and academic assessment tasks, especially in social sciences and humanities. However, the existence of errors, sometimes of great magnitude, has provoked criticism from the academic community. The aim of this article is to carry out an exhaustive bibliographical review of all studies that provide either specific or incidental empirical evidence of the errors found in Google Scholar. The results indicate that the bibliographic corpus dedicated to errors in Google Scholar is still very limited (n=49), excessively fragmented, and diffuse; the findings have not been based on any systematic methodology or on units that are comparable to each other, so they cannot be quantified, or their impact analysed, with any precision. Certain limitations of the search engine itself (time required for data cleaning, limit on citations per search result and hits per query) may be the cause of this absence of empirical studies.Alberto Martin-Martin is on a four-year doctoral fellowship (FPU2013/05863) granted by the Ministerio de Educacion, Cultura y Deportes (Spain). Enrique Orduna-Malea holds a postdoctoral fellowship (PAID-10-14), from the Polytechnic University of Valencia (Spain).Orduña Malea, E.; Martín-Martín, A.; Delgado-López-Cózar, E. (2017). Google Scholar as a source for scholarly evaluation: a bibliographic review of database errors. Revista española de Documentación Científica. 40(4):1-33. https://doi.org/10.3989/redc.2017.4.1500S133404White, B. (2006). Examining the claims of Google Scholar as a serious information source. New Zealand Library & Information Management Journal, 50 (1), 11-24.Wleklinski, J.M. (2005). Studying Google Scholar: wall to wall coverage?. Online, 29 (3), 22-26.Yang, K., & Meho, L. I. (2007). Citation Analysis: A Comparison of Google Scholar, Scopus, and Web of Science. Proceedings of the American Society for Information Science and Technology, 43(1), 1-15. doi:10.1002/meet.1450430118