Abstract

The main results of the book Social networks for scientists: A quantitative survey is discussed. The success or failure of social networks is closely linked to the management and creation of content. The most successful sites are the document sharing sites (ResearchGate, Academia.edu, and Mendeley) because participation is based on the exchange of the main academic outputs: research publications. There are two main types of users: 1) producers, who are the less frequent, employ the network for spreading their results and monitor their impact in the academic community; and 2) viewers are the most and use the sites in order to be updated on new publications. These spaces are being used more for private interests than for collaborative purposes, becoming a kind of Diogenes Club, where most of the users come together in the same virtual space to conduct only private actions.

Abstract

The evolution of the top academic social networks: Mendeley, Academia.edu, and ResearchGate is analyzed. This study tests the current health of these platforms and determines which growth stage they are in by tracking the annual number of new members and documents. In addition, the degree of transparency of these sites is discussed in relation to publicly available information about their services. The results show these platforms are reaching a change in cycle, where the increase rates are slowing down, decreasing the aggregation rate of documents and users.

Abstract

The concept of "big data" is explained as a system of analyzing large amounts of data to discover trends, patterns, correlations and even causality to generate predictions. This discipline can be adapted to the context of the daily work of the information professional dealing with "small data" and web analytics. Examples are provided of tools that support the management and analysis of huge amounts of publicly available data.

Abstract

The origins, disciplinary relationships and main applications of cybermetrics and webometrics are explained, in order to proceed to a discussion of the current situation regarding the methods used for extracting web information and indicators from publicly available sources. We performed a comparative analysis of three techniques to measure the prestige, impact or visibility of academic institutions, including: 1) the survey, limited by its subjectivity and small sample sizes, 2) citation analysis, also hampered by small populations but which offers more reliability because it relies on peer opinions, and 3) link analysis. Link analysis is considered the cornerstone of webometrics and the large numbers involved is to be appreciated. It can identify patterns despite being the method that is most “noisy” because of the richness and diversity of motivations for linking. The unfortunate demise of Yahoo Site Explorer, the main source of information on links, is reported and its absence will force a rethinking of the techniques and a search for alternative sources of this valuable type of data. Some alternatives are studied, including the use of mentions such as titles, names of institutions or individuals and so-called reference or quote URLs, and their advantages and disadvantages are discussed. It is noted that this new approach is especially useful for web 2.0 tools.

Abstract

We discuss the popularity of Cuba’s MES (Ministry of Higher Education) centres, as well as their interconnectedness and visibility on the world wide web. The role of links in the positioning and visibility of these sites was studied because web browsers use link analysis (or hypertext analysis) to infer not only the content but the quality or the possible “authority” status of a web site. A webmetric study of the 17 centres with web sites was conducted. The relationship between the number of links and page traffic of the MES centres was determined by analysis of the browsers Google, Alltheweb, and Altavista, and also from the Internet Archive and Traffic Rank (Alexa ranking). Four results were obtained: i) the MES centres had better visibility in the browser Altavista, with a Standard Error (SE) ±0,00210; of these, a significantly better value was observed for the 13th centre (superscript a); ii) as page storage in the Internet archive increased, more links or cites were received from the browsers; iii) the links and ranking in Alltheweb showed significantly better performance (SE ± 0,23) and a coefficient of determination (R2) of 0,44%; iv) significant differences exist among MES centre sites in the Internet archive, with respect to links and activity reported in the Traffic Rank.

Abstract

Spain’s academic web space is diagrammed, together with its relationship with the European Higher Education Area (EHEA), with the goal of determining the topology, the outstanding universities, and our standing with respect to other European web spaces. Several co-link maps and network graphs visually represent these relationships among universities and web spaces. The results show that the Spanish network is rather isolated from other European universities, because the out- and inlink percentages are quite low considering the volume of content and the number of Spanish universities. On the other hand, Spain’s academic web space is quite cohesive, with a significant nucleus that is strongly interconnected. We conclude that the limited use of the English language and minimal electronic publication of quality research in accessible repositories could explain this isolation. In addition, Spanish universities have a more local than international emphasis.

Abstract

The extensive use of the web by many sectors of society has created the potential for new wider impact indicators. This article reviews research about Google Scholar and Google Patents, both of which can be used as sources of impact indicators for academic articles. It also briefly reviews methods to extract types of links and citations from the web as a whole, although the indicators that these generate are now probably too broad and too dominated by automatically generated websites, such as library and publisher catalogues, to be useful in practice. More valuable web-based indicators can be derived from specific types of web pages that cite academic research, such as online presentations, course syllabi, and science blogs. These provide evidence that is easier to understand and use and less likely to be affected by unwanted types of automatically generated content, although they are susceptible to gaming.

Abstract

This literature review assesses indicators derived from social media sources, including both general and academic sites. Such indicators have been termed altmetrics, influmetrics, social media metrics, or a type of webometric, and have recently been commercialised by a number of companies and employed by some publishers and university administrators. The social media metrics analysed here derive mainly from Twitter, Facebook, Google+, F1000, Mendeley, ResearchGate, and Academia.edu. They have the apparent potential to deliver fast, free indicators of the wider societal impact of research, or of different types of academic impacts, complementing academic impact indicators from traditional citation indexes. Although it is unwise to employ them in formal evaluations with stakeholders, due to their susceptibility to gaming and lack of real evidence that they reflect wider research impacts, they are useful for formative evaluations and to investigate science itself. Mendeley reader counts are particularly promising.

Abstract

Additive Manufacturing (AM) technologies, technologies that produce three-dimensional parts layer by layer from a material, have the potential to revolutionize the paradigm of manufacturing. Furthermore, in recent years AM technologies have sparked intense interest for developing medical implants, devices and scaffolds. In this context, the main objective of this article is to present an overall view of the trends and the impact of the research carried out in AM technologies for biomedical engineering applications. Therefore, to achieve the main objective, a research trend and scientific impact analysis model has been designed and implemented, which carries out a bibliometric indicator analysis, in general, and a web indicator analysis, in particular. The findings obtained will advance the means of visualizing the state of research in AM for biomedical engineering technologies.