This paper examines the co-authorship network of the digital library (DL) research community using social network analysis. The study analyzes the co-authorship network of the ACM, IEEE, and joint ACM/IEEE DL conferences from 1994 to 2004. The authors use two models: a binary undirected network and a weighted directed network. The weighted directed model introduces AuthorRank, a metric that measures the impact of individual authors in the network. The results show that AuthorRank and PageRank outperform traditional centrality metrics like degree, closeness, and betweenness. The study also investigates international participation in the Joint Conference on Digital Libraries (JCDL). The analysis reveals that the DL research community is highly multidisciplinary, with authors from various fields such as databases, networking, and information science. However, the community is fragmented into smaller clusters, with many authors publishing only one paper. The study also finds that the DL research community has a smaller largest component, a higher clustering coefficient, and a longer characteristic path length compared to other co-authorship networks. The results show that PageRank and AuthorRank are more effective in identifying prestigious authors than traditional metrics. The study also validates the results against the JCDL program committee members, showing that the rankings of authors based on PageRank and AuthorRank closely match the committee members. The study concludes that collaboration remains a key factor in DL research, and that the DL research community is still evolving, with rich collaboration patterns across institutional boundaries. The study also highlights the potential applications of the network models in evaluating research impact, guiding conference program committees, and quantifying conference prestige based on their program committees. The weighted model is particularly useful for visualizing co-authorship graphs, allowing important links to be emphasized and trivial links to be truncated. The study also presents an interactive author navigation tool based on the webdot tool of GraphViz. The results show that the DL research community is still developing, with a rich network of collaborations, but with a higher degree of clustering and dispersion than other domains. The study emphasizes the importance of continued emphasis on collaboration to ensure that DL research remains an open, diverse, and well-connected marketplace of ideas.This paper examines the co-authorship network of the digital library (DL) research community using social network analysis. The study analyzes the co-authorship network of the ACM, IEEE, and joint ACM/IEEE DL conferences from 1994 to 2004. The authors use two models: a binary undirected network and a weighted directed network. The weighted directed model introduces AuthorRank, a metric that measures the impact of individual authors in the network. The results show that AuthorRank and PageRank outperform traditional centrality metrics like degree, closeness, and betweenness. The study also investigates international participation in the Joint Conference on Digital Libraries (JCDL). The analysis reveals that the DL research community is highly multidisciplinary, with authors from various fields such as databases, networking, and information science. However, the community is fragmented into smaller clusters, with many authors publishing only one paper. The study also finds that the DL research community has a smaller largest component, a higher clustering coefficient, and a longer characteristic path length compared to other co-authorship networks. The results show that PageRank and AuthorRank are more effective in identifying prestigious authors than traditional metrics. The study also validates the results against the JCDL program committee members, showing that the rankings of authors based on PageRank and AuthorRank closely match the committee members. The study concludes that collaboration remains a key factor in DL research, and that the DL research community is still evolving, with rich collaboration patterns across institutional boundaries. The study also highlights the potential applications of the network models in evaluating research impact, guiding conference program committees, and quantifying conference prestige based on their program committees. The weighted model is particularly useful for visualizing co-authorship graphs, allowing important links to be emphasized and trivial links to be truncated. The study also presents an interactive author navigation tool based on the webdot tool of GraphViz. The results show that the DL research community is still developing, with a rich network of collaborations, but with a higher degree of clustering and dispersion than other domains. The study emphasizes the importance of continued emphasis on collaboration to ensure that DL research remains an open, diverse, and well-connected marketplace of ideas.