Purpose Universities play an important role in the promotion and implementation of the 2030 Agenda for Sustainable Development. This study aims to examine the visibility of information about the Sustainable Development Goals (SDGs) on the websites of Spanish and major international universities, by means of a quantitative and qualitative analysis with an online visibility management platform that makes use of big data technology. Design/methodology/approach The Web visibility of the universities studied in relation to the terms “SDG”, “Sustainable Development Goals” and “2030 Agenda” was determined using the SEMrush tool. Information was obtained on the number of web pages accessed and the queries formulated (query expansion). The content indexed by Google for these universities was compiled, and finally, the search engine optimization (SEO) factors applicable to the websites with the highest Web visibility were identified. Findings The universities analysed are content creators but do not have very high Web visibility in Web searches for information on the SDGs. Of the 98 universities analysed, only four feature prominently in search results. Originality/value Although research exists on the application of SEO to different areas, there have not, to date, been any studies examining the Web visibility of universities in relation to Web searches for information on the 2030 Agenda. The main contributions of this study are the global perspective it provides on the Web visibility of content produced by universities about the SDGs and the recommendations it offers for improving that visibility.
La pandemia derivada de la COVID-19 ha afectado a todos los sectores de nuestra sociedad; desde la economía a la cultura, pasando por la educación o el tema crítico de la salud. El tratamiento de la prensa de un país puede ser un buen indicador para saber cuáles son las preocupaciones y los intereses de los ciudadanos. Siguiendo ese indicador, el objetivo de este trabajo es intentar analizar la prensa europea durante un periodo concreto para poder identificar esas preocupaciones e intereses nacionales y analizar las diferencias existentes entre el grupo de los países más afectados por la pandemia y el grupo de los países menos golpeados por la misma. Se ha utilizado la base de datos de noticias Factiva de Dow Jones & Reuters para obtener las noticias y los titulares publicados por los seis países analizados durante un mes. El grupo 1 de países, los más afectados, está formado por Italia, España y Bélgica; el grupo 2 son Alemania, Austria e Irlanda. Los resultados muestran que el grado de afectación por la COVID-19 ha marcado el tratamiento ofrecido por la prensa a la cobertura de la crisis sanitaria, tanto en lo que se refiere a los temas y al número de noticias publicadas, como a la concentración que se produce en los medios y en los autores.
Purpose-Controlled vocabularies play an important role in information retrieval. Numerous studies have shown that conceptual searches based on vocabularies are more effective than keyword searches, at least in certain contexts. Consequently, new ways must be found to improve controlled vocabularies. This paper presents a semi-automatic model for updating controlled vocabularies through the use of a text corpus and the analysis of query logs. Design/methodology/approach-An experimental development is presented in which, first, the suitability of a controlled vocabulary to a text corpus is examined. The keywords entered by users to access the text corpus are then compared with the descriptors used to index it. Finally, both the query logs and text corpus are processed to obtain a set of candidate terms to update the controlled vocabulary. Findings-This paper describes a model applicable both in the context of the text corpus of an online academic journal and to repositories and intranets. The model is able to: a) identify the queries that led users from a search engine to a relevant document; and b) process these queries to identify candidate terms for inclusion in a controlled vocabulary. Originality/value-The proposed model takes into account the perspective of users by mining queries in order to propose candidate terms for inclusion in a controlled vocabulary. Research limitations/implications-Ideally, the model should be used in controlled Web environments, such as repositories, intranets or academic journals. Social implications-The proposed model directly improves the indexing process by facilitating the maintenance and updating of controlled vocabularies. It so doing, it helps to optimise access to information.
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