The field of digital libraries (DLs) coalesced in 1994: the first digital library conferences were held that year, awareness of the World Wide Web was accelerating, and the National Science Foundation awarded @math AuthorRank$ as an indicator of the impact of an individual author in the network. The results are validated against conference program committee members in the same period. The results show clear advantages of PageRank and AuthorRank over degree, closeness and betweenness centrality metrics. We also investigate the amount and nature of international participation in Joint Conference on Digital Libraries (JCDL).
An early example of a co-authorship network is the Erd " o s Number Project, in which the smallest number of co-authorship links between any individual mathematician and the Hungarian mathematician Erd " o s are calculated @cite_23 . (A mathematician's Erd " o s Number'' is analogous to an actor's Bacon Number''.) Newman studied and compared the co-authorship graph of arXiv, Medline, SPIRES, and NCSTRL @cite_19 @cite_3 and found a number of network differences between experimental and theoretical disciplines. Co-authorship analysis has also been applied to various ACM conferences: Information Retrieval (SIGIR) @cite_9 , Management of Data (SIGMOD) @cite_17 and Hypertext @cite_14 , as well as mathematics and neuroscience @cite_6 , information systems @cite_5 , and the field of social network analysis @cite_27 . International co-authorship networks have been studied in Journal of American Society for Information Science & Technology (JASIST) @cite_4 and Science Citation Index @cite_33 .
@cite_14 @cite_4 @cite_33 @cite_9 @cite_3 @cite_6 @cite_19 @cite_27 @cite_23 @cite_5 @cite_17
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This paper presents the analysis and modelling of two data sets associated with the literature of hypertext as represented by the ACM Hypertext conference series. This work explores new ways of organising and accessing the vast amount of interrelated information. The first data set, including all the full papers published in this series (1987 1998), is structured and visualised as a semantic space. This semantic space provides an access point for each paper in this collection. The second data set, containing author co-citation counts based on nine conferences in the series (1989 1998), is analysed and mapped in its entirety and in three evenly distributed sub-periods. Specialties  major research fronts in the field of hypertext  are identified based on the results of a factor analysis and corresponding author co-citation maps. The names of authors in these maps are linked to the bibliographical and citation summaries of these authors on the WWW. This article reports findings from a study of the geographic distribution of foreign authors in the Journal of American Society for Information Science & Technology (JASIST) and Journal of Documentation (JDoc). Bibliographic data about foreign authors and their geographic locations from a 50-year publication period (1950-1999) are analyzed per 5-year period for both JASIST and JDoc. The distribution of foreign authors by geographic locations was analyzed for the overall trends in JASIST and JDoc. UK and Canadian authors are the most frequent foreign authors in JASIST. Authors from the United States and Canada are the most frequent foreign authors in JDoc. The top 10 geographic locations with highest number of foreign authors and the top 10 most productive foreign authors were also identified and compared for their characteristics and trends. As part of the celebration of twenty-five years of ACM SIGIR conferences we performed a content analysis of all papers published in the proceedings of SIGIR conferences, including those from 2002. From this we determined, using information retrieval approaches of course, which topics had come and gone over the last two and a half decades, and which topics are currently "hot". We also performed a co-authorship analysis among authors of the 853 SIGIR conference papers to determine which author is the most "central" in terms of a co-authorship graph and is our equivalent of Paul Erdos in Mathematics. In the first section we report on the content analysis, leading to our prediction as to the most topical paper likely to appear at SIGIR2003. In the second section we present details of our co-authorship analysis, revealing who is the "Christopher Lee" of SIGIR, and in the final section we give pointers to where readers who are SIGIR conference paper authors may find details of where they fit into the coauthorship graph. Using data from computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. We have studied many statistical properties of our networks, including numbers of papers written by authors, numbers of authors per paper, numbers of collaborators that scientists have, typical distance through the network from one scientist to another, and a variety of measures of connectedness within a network, such as closeness and betweenness. We further argue that simple networks such as these cannot capture the variation in the strength of collaborative ties and propose a measure of this strength based on the number of papers coauthored by pairs of scientists, and the number of other scientists with whom they worked on those papers. Using a selection of our results, we suggest a variety of possible ways to answer the question, "Who is the best connected scientist?" We analyze growing networks ranging from collaboration graphs of scientists to the network of similarities defined among the various transcriptional profiles of living cells. For the explicit demonstration of the scale-free nature and hierarchical organization of these graphs, a deterministic construction is also used. We demonstrate the use of determining the eigenvalue spectra of sparse random graph models for the categorization of small measured networks. Social network analysis (SNA) is not a formal theory in sociology but rather a strategy for investigating social structures. As it is an idea that can be applied in many fields, we study, in partic...