Are web mentions accurate substitutes for inlinks for Spanish universities?

• Autores: José Luis Ortega Priego, Enrique Orduña Malea, Isidro F. Aguillo Caño
• Localización: Online Information Review, ISSN-e 1468-4535, Vol. 38, Nº. 1, 2014, págs. 59-77
• Idioma: inglés
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• Dialnet Métricas: 1 Cita
• Resumen

  • Purpose � 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.