Presencia y visibilidad web de las universidades públicas españolas

Ontalba-Ruipérez

2012

Scientometrics

Self Cite

PREPRINT. Please cite as: Orduña-Malea, E., Ontalba-Ruipérez, J-A. (2013). Selective linking from social platforms to university websites: a case study of the Spanish academic system. Scientometrics, v. 95(2) Abstract Mention indicators have frequently been used in Webometric studies because they provide a powerful tool for determining the degree of visibility and impact of web resources. Among mention indicators, hypertextual links were a central part of many studies until Yahoo! discontinued the 'linkdomain' command in 2011. Selective links constitute a variant of external links where both the source and target of the link can be selected. This paper intends to study the influence of social platforms (measured through the number of selective external links) on academic environments, in order to ascertain both the percentage that they constitute and whether some of them can be used as substitutes of total external links. For this purpose, 141 URLs belonging to 76 Spanish universities were compiled in 2010 (before Yahoo! stopped their link services), and the number of links from 13 selected social platforms to these universities were calculated. Results confirm a good correlation between total external links and links that come from social platforms, with the exception of some applications (such as Digg and Technorati). For those universities with a higher number of total external links, the high correlation is only maintained on Delicious and Wikipedia, which can be utilized as substitutes of total external links in the context analyzed. Notwithstanding, the global percentage of links from social platforms constitute only a small fraction of total links, although a positive trend is detected, especially in services such as Twitter, Youtube, and Facebook.

Section: Discussionmentioning

confidence: 97%

Selective linking from social platforms to university websites: a case study of the Spanish academic system

Ontalba-Ruipérez

2012

Scientometrics

Self Cite

“…Later, the mean of the v sn values for each sampling month was calculated and a value between 0 and 100 was also obtained; this was called the “mean relative representativeness factor for page count or size (Rs).” This factor could be calculated for any group of the websites sampled and for any period of time. Moreover, by substituting the overall page count value for that of the number of links ( v vn ), the Rv value could be obtained for the same set of URLs (Orduña‐Malea, Serrano‐Cobos, Ontalba‐Ruipérez, & Lloret‐Romero, ).…”

Section: Methodsmentioning

confidence: 99%

Aggregation of the web performance of internal university units as a method of quantitative analysis of a university system: The case of Spain

2013

J Am Soc Inf Sci Tec

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PREPRINT. Please cite as: Orduña-Malea, E. (2013). Aggregation of the web performance of internal university units as a method of quantitative analysis of a university system: the case of Spain. Journal of the American Society for Information Science and Technology, 64(10), 2100-2114. doi: http://dx.doi.org/10.1002/asi.22912 Abstract: The aggregation of web performance (page count and visibility) of internal university units could constitute a more precise indicator than the overall web performance of the universities and, therefore, be of use in the design of university web rankings. In order to test this hypothesis, a longitudinal analysis of the internal units of the Spanish university system was conducted over the course of 2010. For the 13,800 URLs identified, page count and visibility was calculated using the Yahoo! API.The internal values obtained were aggregated by university and compared with the values obtained from the analysis of the universities' general URLs. The results indicate that, although the correlations between general and internal values are high, internal performance is low in comparison to general performance, and that they give rise to different performance rankings. The conclusion is that the aggregation of unit performance is of limited use due to the low levels of internal development of the websites, and so its use is not recommended for the design of rankings. Despite this, the internal analysis enabled the detection of, amongst other things, a low correlation between page count and visibility due to the widespread use of subdirectories and problems accessing certain content.

“…Search (and the associated platform, Yahoo! Site Explorer), Exalead became the only search engine that supports link search commands, but its limited geographical coverage prevents it being used globally (Orduña‐Malea, Serrano‐Cobos, Ontalba‐Ruipérez, & Lloret‐Romero, ). On the other hand, new services are appearing that supply the links received by a particular website; these include MajesticSEO, Ahrefs, and Open Site Explorer .…”

Section: Alternatives For Link Analysismentioning

confidence: 99%

Hyperlinks embedded in twitter as a proxy for total external in‐links to international university websites

Asso for Info Science & Tech

Torres‐Salinas

López-Cózar

2015

Self Cite

Twitter as a potential alternative source of external links for use in webometric analysis is analyzed because of its capacity to embed hyperlinks in different tweets. Given the limitations on searching Twitter's public application programming interface (API), we used the Topsy search engine as a source for compiling tweets. To this end, we took a global sample of 200 universities and compiled all the tweets with hyperlinks to any of these institutions. Further link data was obtained from alternative sources (MajesticSEO and OpenSiteExplorer) in order to compare the results. Thereafter, various statistical tests were performed to determine the correlation between the indicators and the possibility of predicting external links from the collected tweets. The results indicate a high volume of tweets, although they are skewed by the performance of specific universities and countries. The data provided by Topsy correlated significantly with all link indicators, particularly with OpenSiteExplorer (r = 0.769). Finally, prediction models do not provide optimum results because of high error rates. We conclude that the use of Twitter (via Topsy) as a source of hyperlinks to universities produces promising results due to its high correlation with link indicators, though limited by policies and culture regarding use and presence in social networks.