Motivated by the merging of four Swedish counties to a larger administrative and political unit with increased responsibilities,
a comprehensive study of regional–foreign research collaboration was carried out. Various multivariate methods were applied
for the depiction of collaborative networks of various compositions and at various levels of aggregation. Other aspects investigated
concerned the influence of institutions and countries on regional–foreign collaboration and the relation between collaboration
and research fields. Findings showed that foreign research collaboration was concentrated to three major regional institutions,
each with a characteristic collaborative context. The influence of domestic collaboration was notable with regard to medical
research while collaboration within the field of physics and astronomy was characteristic for pure regional–foreign collaboration,
which was the dominating type of research collaboration throughout the period of observation (1998–2006).
Summary This paper builds on previous research concerned with the classification and specialty mapping of research fields. Two methods are put to test in order to decide if significant differences as to mapping results of the research front of a science field occur when compared. The first method was based on document co-citation analysis where papers citing co-citation clusters were assumed to reflect the research front. The second method was bibliographic coupling where likewise citing papers were assumed to reflect the research front. The application of these methods resulted in two different types of aggregations of papers: (1) groups of papers citing clusters of co-cited works and (2) clusters of bibliographically coupled papers. The comparision of the two methods as to mapping results was pursued by matching word profiles of groups of papers citing a particular co-citation cluster with word profiles of clusters of bibliographically coupled papers. Findings suggested that the research front was portrayed in two considerably different ways by the methods applied. It was concluded that the results in this study would support a further comparative study of these methods on a more detailed and qualitative ground. The original data set encompassed 73,379 articles from the fifty most cited environmental science journals listed in Journal Citation Report, science edition downloaded from the Science Citation Index on CD-ROM.
The method of author cocitation analysis (ACA) was first presented by White and Griffith in 1981 as a “literature measure
of intellectual structure” and its applicability for the mapping of areas of science has since then been tested in various
bibliometric science mapping studies. In this study, an experimental method of calculating the first or single author cocitation
frequency is presented and compared with the standard method. Applying Ward’s method of clustering, the analysis revealed
that the two approaches did not produce similar results and a tentative interpretation of deviations was that the experimental
method provided with a more detailed depiction of the specialty structure. It was also concluded that a number of additional
research questions need to be resolved before a comprehensive understanding of the suggested method’s merits and demerits
This paper presents a citation analysis of the cognitive structure of current cardiovascularresearch. Used methods are co-citation analysis, bibliographic coupling and quantitative analysisof title words. Tables and graphs reveal: (1) The journal co-citation structure; (2) the cognitivecontent and the bibliometric structure of clusters based on co-citation; (3) the cognitive contentand the bibliometric structure of clusters based on bibliographic coupling. A predominance ofdifferent research aspects on coronary artery disease was found in clusters based on co-citations aswell as in clusters based on bibliographic coupling.
This paper deals with two document-document similarity approaches in the context of science mapping: bibliographic coupling
and a text approach based on the number of common abstract stems. We used 43 articles, published in the journal Information Retrieval, as test articles. An information retrieval expert performed a classification of these articles. We used the cosine measure
for normalization, and the complete linkage method was used for clustering the articles. A number of articles pairs were ranked
(1) according to descending normalized coupling strength, and (2) according to descending normalized frequency of common abstract
stems. The degree of agreement between the two obtained rankings was low, as measured by Kendall’s tau. The agreement between
the two cluster solutions, one for each approach, was fairly low, according to the adjusted Rand index. However, there were
examples of perfect agreement between the coupling solution and the stems solution. The classification generated by the expert
contained larger groups compared to the coupling and stems solutions, and the agreement between the two solutions and the
classification was not high. According to the adjusted Rand index, though, the stems solution was a better approximation of
the classification than the coupling solution. With respect to cluster quality, the overall Silhouette value was slightly
higher for the stems solution. Examples of homogeneous cluster structures, as well as negative Silhouette values, were found
with regard to both solutions. The expert classification indicates that the field of information retrieval, as represented
by one volume of articles published in Information Retrieval, is fairly heterogeneous regarding research themes, since the classification is associated with 15 themes. The complete linkage
method, in combination with the upper tail rule, gave rise to a fairly good approximation of the classification with respect
to the number of identified groups, especially in case of the stems approach.