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The purpose of this paper is to visualize the structure of SCImago Journal & Country Rank (SJR) coverage of the extensive citation network of Scopus journals, examining this bibliometric portal through an alternative approach, applying clustering and visualization techniques to a combination of citation-based links.

Three SJR journal-journal networks containing direct citation, co-citation and bibliographic coupling links are built. The three networks were then combined into a new one by summing up their values, which were later normalized through geo-normalization measure. Finally, the VOS clustering algorithm was executed and the journal clusters obtained were labeled using original SJR category tags and significant words from journal titles.

The resultant scientogram displays the SJR structure through a set of communities equivalent to SJR categories that represent the subject contents of the journals they cover. A higher level of aggregation by areas provides a broad view of the SJR structure, facilitating its analysis and visualization at the same time.

This is the first study using Persson’s combination of most popular citation-based links (direct citation, co-citation and bibliographic coupling) in order to develop a scientogram based on Scopus journals from SJR. The integration of the three measures along with performance of the VOS community detection algorithm gave a balanced set of clusters. The resulting scientogram is useful for assessing and validating previous classifications as well as for information retrieval and domain analysis.

This study aimed to examine the similarities and differences between the ability to analyze the environment and exploit new knowledge (absorptive capacity) and the skills to generate value from innovation (appropriation). These fields have similar origins and are sometimes confused by practitioners and academics.

A review was conducted based on a full-text analysis of 681 and 431 papers on appropriation and absorptive capacity, respectively, from Scopus, Science Direct and Lens, using methodologies such as text mining, backward citation analysis, modularity clustering and latent Dirichlet allocation analysis.

In business disciplines, the fields are considered different; however, in other disciplines, it was found that some authors defined them quite similarly. The citation analysis results showed that appropriation was more relevant to absorptive capacity, or vice versa. From the dimension perspective, it was found that although appropriation was considered a relevant element for absorptive capacity, the last models did not include it. Finally, it was found that studies on both topics identified the importance of appropriation and absorptive capacity for innovation performance, knowledge management and technology transfer.

This is one of the first studies to examine in-depth the relationship between appropriation and absorptive capacity, bridging a gap in both fields.

The purpose of this paper is to visualize the inter‐university and international collaboration networks generated by Spanish universities based on the co‐authorship of scientific articles.

The approach takes the form of formulation based on a bibliometric analysis of Spanish university production from 2000 to 2004 as contained in Web of Science databases, applying social network visualization techniques. The co‐authorship data used were extracted with the total counting method from a database containing 100,710 papers.

Spanish inter‐university collaboration patterns appear to be influenced by both geographic proximity and administrative and political affiliation. Inter‐regional co‐authorship encompasses regional sub‐networks whose spatial scope conforms rather closely with Spanish geopolitical divisions. Papers involving international collaboration are written primarily with European Union and North and Latin American researchers. Greater visibility is attained with international co‐authorship than with any other type of collaboration studied.

Impact was measured in terms of journals rather than each individual paper. The co‐authorship data were taken from the Web of Knowledge and were not compared with data from other databases.

The data obtained in the paper may provide guidance for public policy makers seeking to enhance and intensify the internationalization of scientific production in Spanish universities.

The Spanish university system is in the midst of profound structural change. This is the first paper to describe Spanish university collaboration networks using social network visualization techniques, covering an area not previously addressed.

Although the role of enterprise in R&D is broadly acknowledged, few attempts have been made to gather data for analyzing the nature and scope of private sector collaboration. This study aims to deliver empirical results based on quantitative data to gain insight into the role of private enterprise as an indispensable actor in scientific development and innovation.

The study aimed to deliver empirical results based on quantitative data to gain insight into the role of private enterprise as an indispensable actor in scientific development and innovation. To this end, an analysis was conducted of the contribution made by Spanish business, focusing on the 50 most active companies in terms of internationally visible scientific output, from three perspectives.

The findings provide insight into business involvement in the R&D system based on: research papers published; national, international and sectoral collaboration patterns; structural patterns; and the identification of the most prominent companies from a systematic comparison of their research results and their position in the resulting collaboration network.

Bibliometric analyses do not measure all types of publications. Indicators are usually based on data in the Thomson Reuters databases, which are regarded as being representative of peer‐reviewed, publicly accessible papers with high international visibility and impact. The Thomson Reuters databases feature a series of advantages that make them indispensable for studies on scientific collaboration.

One of the core ideas of this study is the emphasis on the essential role of collaboration in improving scientific results, as borne out by the correlation between the clustering coefficient and the hybrid indicators. The findings also provide proof of the success of strategies for institutional collaboration. The foregoing shows that the application of hybrid indicators to institutional aggregates yields novel results not explored in preceding studies.

The web application presented in this paper allows for an analysis to reveal centres of excellence in different fields worldwide using publication and citation data. Only specific aspects of institutional performance are taken into account and other aspects such as teaching performance or societal impact of research are not considered. The purpose of this paper is to address these issues.

Based on data gathered from Scopus, field-specific excellence can be identified in institutions where highly-cited papers have been frequently published.

The web application (www.excellencemapping.net) combines both a list of institutions ordered by different indicator values and a map with circles visualising indicator values for geocoded institutions.

Compared to the mapping and ranking approaches introduced hitherto, our underlying statistics (multi-level models) are analytically oriented by allowing the estimation of values for the number of excellent papers for an institution which are statistically more appropriate than the observed values; the calculation of confidence intervals as measures of accuracy for the institutional citation impact; the comparison of a single institution with an “average” institution in a subject area: and the direct comparison of at least two institutions.

This article aims to display the structure and reveal the web influence of institutions in the MENA zone, in geographic terms (country) and academic terms (universities), by means of their links.

Using search engines and webcrawlers designed to gather information about web links, in conjunction with visualization techniques and degree indicators based on social network analysis, the authors achieved their objective and found responses to a series of pertinent research questions.

There is no direct relationship between the number of university websites and the number of inlinks. Linking between countries in the MENA zone obeys patterns of vicinity and geopolitics. Arab universities are interlinked following trends governed by territorial proximity. There is a strong endogamic tendency, with universities from a single country citing each other, particularly in the case of Saudi Arabia. The authors present the first ranking of web influence in the MENA zone based on network indicators, namely country and university, and their order is corroborated by comparison with other rankings of a webometric or scientometric nature.

Studies of this type cannot be undertaken again, at least not from the web link perspective, as Yahoo!, Google and Bing have since blocked the webcrawlers that attempt to carry out searches of inlinking or co-inlinking between/among sites. Hence, this work can be considered both a pioneer and the last of its kind. The authors do not know if or when it will be possible to again make queries about URLs in webs or, alternatively, in titles.

This is the first visual report of the web structure underlying the countries and universities of the MENA zone. It is also the first time that a country and university ranking of this geopolitical zone has been carried out using network indicators based on web links.

Gene term variation is a shortcoming in text‐mining applications based on biomedical literature‐based knowledge discovery. The purpose of this paper is to propose a technique for normalizing gene names in biomedical literature.

Under this proposal, the normalized forms can be characterized as a unique gene symbol, defined as the official symbol or normalized name. The unification method involves five stages: collection of the gene term, using the resources provided by the Entrez Gene database; encoding of gene‐naming terms in a table or binary matrix; design of a parametrized finite‐state graph (P‐FSG); automatic generation of a dictionary; and matching based on dictionary look‐up to transform the gene mentions into the corresponding unified form.

The findings show that the approach yields a high percentage of recall. Precision is only moderately high, basically due to ambiguity problems between gene‐naming terms and words and abbreviations in general English.

The major limitation of this study is that biomedical abstracts were analyzed instead of full‐text documents. The number of under‐normalization and over‐normalization errors is reduced considerably by limiting the realm of application to biomedical abstracts in a well‐defined domain.

The system can be used for practical tasks in biomedical literature mining. Normalized gene terms can be used as input to literature‐based gene clustering algorithms, for identifying hidden gene‐to‐disease, gene‐to‐gene and gene‐to‐literature relationships.

Few systems for gene term variation handling have been developed to date. The technique described performs gene name normalization by dictionary look‐up.

The study looks at how well the distribution of “sitations” (inlinks received by Web spaces) fits either a power law (of the Lotka type) or a bibliometric distribution for printed publications (of the Bradford type). The experimental sample examines the sitations found in a closed generic environment of thematically‐related Web sites – the case of Extremadura (Spain). Two sets of data, varying several parameters, were used. The sitation distributions found were coherent with those described in previous experiments of this type, including in the exponent. The plots of accumulated clusters of sitations and targets, however, did not fit the typical Bradford distribution.

To propose a categorization of the different conflation procedures at the two basic approaches, non‐linguistic and linguistic techniques, and to justify the application of normalization methods within the framework of linguistic techniques.

Presents a range of term conflation methods, that can be used in information retrieval. The uniterm and multiterm variants can be considered equivalent units for the purposes of automatic indexing. Stemming algorithms, segmentation rules, association measures and clustering techniques are well evaluated non‐linguistic methods, and experiments with these techniques show a wide variety of results. Alternatively, the lemmatisation and the use of syntactic pattern‐matching, through equivalence relations represented in finite‐state transducers (FST), are emerging methods for the recognition and standardization of terms.

The survey attempts to point out the positive and negative effects of the linguistic approach and its potential as a term conflation method.

Outlines the importance of FSTs for the normalization of term variants.

To evaluate the accuracy of conflation methods based on finite‐state transducers (FSTs).

Incorrectly lemmatized and stemmed forms may lead to the retrieval of inappropriate documents. Experimental studies to date have focused on retrieval performance, but very few on conflation performance. The process of normalization we used involved a linguistic toolbox that allowed us to construct, through graphic interfaces, electronic dictionaries represented internally by FSTs. The lexical resources developed were applied to a Spanish test corpus for merging term variants in canonical lemmatized forms. Conflation performance was evaluated in terms of an adaptation of recall and precision measures, based on accuracy and coverage, not actual retrieval. The results were compared with those obtained using a Spanish version of the Porter algorithm.

The conclusion is that the main strength of lemmatization is its accuracy, whereas its main limitation is the underanalysis of variant forms.

The report outlines the potential of transducers in their application to normalization processes.